Predictability of the rate of seismic energy in North America

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Abstract


The predictability of the rate of seismicity and strong earthquakes of North America is assessed based on the catalog of the U.S. Geological Survey for 1900–2016. A second-order nonlinear differential equation is used as the mathematical model of the study; the algorithms for optimization and predictability assessment are developed by the author. The conducted estimates show high predictability of the rate of seismic energy. Among 1422 analyzed strong earthquakes, the foreshock predictability is revealed for 120 earthquakes (215 thousand determinations) and the aftershock predictability for 1410 earthquakes (more than 3 million determinations). The predictability related to the strong earthquakes appears at small (1.5–3 km) radius of the samples of hypocenters and increases in terms of the number of the predicted earthquakes with the increase in the radius of the samples. The forecast distances in time are, on average, tens of days for foreshock predictability and thousands of days for aftershock predictability. The obtained results demonstrate a very promising potential of the approximation-extrapolation approach for forecasting both the strong earthquakes themselves and the subsequent aftershock decay of seismic activity.


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ВВЕДЕНИЕ

Прогноз таких природных катастроф, как извержения вулканов и разрушительные землетрясения, является фундаментальной научной проблемой, с древнейших времен привлекающей внимание исследователей. Однако несмотря на пристальное внимание, эта проблема по-прежнему далека от разрешения. Как отмечается в работе [Чебров и др., 2011, с. 269], «при всем обилии проведенных и проанализированных наблюдений в мире, место, время и магнитуда будущих разрушительных землетрясений даже в хорошо изученных регионах по-прежнему оказываются неожиданными». С современным состоянием проблемы можно ознакомиться в [Encyclopedia…, 2016].

Данная работа представляет собой развитие методов саморазвивающихся процессов и картирования сейсмической активности по плотности сейсмического потока [Тихонов, 2006; 2009]. Автор этих строк, являясь первоначальным разработчиком обоих вышеупомянутых методов, ни в коем случае не претендует на окончательное решение при их помощи проблемы прогноза природных катастроф, преследуя более скромные цели MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ оценить прогнозные возможности уравнения динамики саморазвивающихся природных процессов (уравнения ДСПП, см. ниже) и, в случае положительных перспектив, довести вышеупомянутые методы до стадии пригодности к практическому использованию. Подобная формулировка задачи предполагает постановку двух групп вопросов. Первая (оценочная) группа определяет правомерность самой постановки задачи прогноза при помощи указанных методов (насколько адекватно использование метода саморазвивающихся процессов при прогнозе потока сейсмической энергии? Как соотносятся с прогнозируемостью сейсмического потока входящие в его состав сильные землетрясения?). Вторая группа вопросов соответствует изучению перспектив практического использования прогнозируемости сейсмического потока (возможно ли заблаговременное выделение зон активизации, предшествующей сильным землетрясениям? Возможен ли количественный прогноз усиления сейсмической активности в этих зонах? и др.). Естественно, что постановка практических вопросов правомерна лишь после получения ответов на вопросы первой группы. Поэтому первоначально предлагается абстрагироваться от прогноза сильных землетрясений и сконцентрировать внимание на прогнозируемости потока энергии землетрясений E, затем рассмотреть взаимосвязь прогнозируемости этого параметра с сильными землетрясениями, и, при наличии взаимосвязи, обсудить перспективы ее использования в прогнозах сильных землетрясений и афтершокового затухания сейсмичности.

Для расчета потока сейсмической энергии используется стандартная информация, содержащаяся в каталогах землетрясений: время начала землетрясения, положение его гипоцентра и энергетическая характеристика (магнитуда или энергетический класс). Положение гипоцентра характеризуется центральной точкой, данные о которой в современных каталогах приводятся с точностью 100 ì. MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaacdaaeaaaaaaaaa8qacqWF8iIFcaaIXaGaaGimaiaa icdacaqGGaacbaGaa4h7aiaab6caaaa@4445@ Однако ошибка определения гипоцентра индивидуальна для каждого землетрясения. Она зависит от силы землетрясения, его положения относительно регистрирующей сети, плотности самой сети и используемых годографов. Учесть ошибку определения каждого гипоцентра в расчетах потока энергии не представляется возможным, поэтому в используемой методике она рассматривается как неизвестный случайный фактор. Ситуация с ошибками определения энергетической характеристики землетрясения аналогична. Поэтому для объективной оценки как прогнозных возможностей, так и перспектив их практического использования подобный анализ предполагается выполнить по нескольким регионам на основе (по возможности) различных источников сейсмических данных в виде нескольких однотипных работ, имеющих разное региональное содержание. Также это позволит собрать большой объем статистических данных, необходимый для следующего этапа исследований.

К настоящему времени подобное исследование выполнено для сейсмичности Камчатки по данным регионального каталога [Малышев, 2019], для потока сейсмической энергии северо-западного обрамления Тихого океана [Малышев, Малышева, 2018], Южной Европы и Средиземноморья по данным каталога Геологической службы США, а также для сейсмичности Японии по данным каталога Японского метеорологического агентства.

Таким образом работа, во-первых, предполагает дать ответ на вопрос, есть ли вообще смысл в использовании уравнения ДСПП в целях прогноза, во-вторых, в ряду с несколькими аналогичными работами обеспечивает набор статистики прогнозируемости потока энергии в различных регионах и по данным различных информационных источников. На следующем этапе исследований анализ этой статистики позволит определить при каких параметрах уравнения и условиях формирования выборок отмечается наилучшая экстраполируемость потока сейсмической энергии. Третий этап исследований предусматривает использование полученных статистических данных для обеспечения устойчивой экстраполяции потока энергии в 3D-пространстве, включая выделение потенциально опасных областей с риском сильных землетрясений. И лишь после этого, на четвертом этапе исследований, можно будет приступить к прогнозу сейсмической активности как в реальном времени, так и в ретроспективе.

МЕТОДЫ ИССЛЕДОВАНИЯ

В работе используется уравнение ДСПП [Малышев, 1991; 2000; 2005]

x =k| x λ x 0 λ | α/λ , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbayaacqGH9aqpcaWGRbWd aiaacYhadaqadaqaa8qaceWG4bGbauaaa8aacaGLOaGaayzkaaWaaW baaSqabeaapeGaeq4UdWgaaOGaeyOeI0YdamaabmaabaWdbiqadIha gaqba8aadaWgaaWcbaWdbiaaicdaa8aabeaaaOGaayjkaiaawMcaam aaCaaaleqabaWdbiabeU7aSbaak8aacaGG8bWaaWbaaSqabeaapeGa eqySdeMaai4laiabeU7aSbaak8aacaGGSaaaaa@536E@ (1)

где: x MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ расчетная характеристика процесса, моделирующая имеющиеся фактические данные; x MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaaaaa@3EEA@ и x MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbayaaaaa@3EEB@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ ее первая и вторая производные по времени t; k MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ коэффициент пропорциональности, а показатели степени λ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaH7oaBaaa@3F95@ и α MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaeqySdegaaa@3F60@ определяют нелинейность процесса, соответственно, в окрестностях стационарного состояния ( x x 0 ) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGabmiEayaafaGaeyisISRa bmiEayaafaWdamaaBaaaleaapeGaaGimaaWdaeqaaOGaaiykaaaa@441B@ и на значительном от него удалении ( x >> x 0 ). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGabmiEayaafaGaeyOpa4Ja eyOpa4JabmiEayaafaWdamaaBaaaleaapeGaaGimaaWdaeqaaOGaai ykaiaac6caaaa@452C@

Уравнение (1) было получено в результате обобщения эмпирически установленных закономерностей различных природных процессов [Малышев, 1991], а его логический смысл сводится к сделанному в терминах теории подобия предположению [Малышев, 2000] о том, что в случае саморазвивающихся процессов, «силы», возникающие при отклонении системы от стационарного состояния, формируются за счет развития самой системы и пропорциональны разности «энергии движения» системы в текущем и стационарном состояниях: F x =a| E x E 0 | γ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGgbWdamaaBaaaleaapeGaamiE aaWdaeqaaOWdbiabg2da9iaadggapaGaaiiFa8qacaWGfbWdamaaBa aaleaapeGaamiEaaWdaeqaaOWdbiabgkHiTiaadweapaWaaSbaaSqa a8qacaaIWaaapaqabaGccaGG8bWaaWbaaSqabeaapeGaeq4SdCgaaa aa@4B1C@ или m x x = a| m x x 2 / 2 m x x 0 2 / 2 | γ . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGTbWdamaaBaaaleaapeGaamiE aaWdaeqaaOWdbiqadIhagaqbaiabg2da9maalyaabaWaaSGbaeaaca WGHbWdaiaacYhapeGaamyBa8aadaWgaaWcbaWdbiaadIhaa8aabeaa kmaabmaabaWdbiqadIhagaqbaaWdaiaawIcacaGLPaaadaahaaWcbe qaa8qacaaIYaaaaaGcbaqcL9vacaaIYaGccqGHsislcaWGTbWdamaa BaaaleaapeGaamiEaaWdaeqaaOWaaeWaaeaapeGabmiEayaafaaapa GaayjkaiaawMcaamaaDaaaleaacaaIWaaabaGaaGOmaaaaaaaak8qa baGaaGOma8aacaGG8bWaaWbaaSqabeaapeGaeq4SdCgaaaaakiaac6 caaaa@5838@ Здесь m x , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGTbWdamaaBaaaleaapeGaamiE aaWdaeqaaOWdbiaacYcaaaa@40F4@ F x MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbiqaaW7cqaaaaaaaaaWdbiaadAeapaWaaSbaaSqaa8qa caWG4baapaqabaaaaa@40CD@ и E x , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGfbWdamaaBaaaleaapeGaamiE aaWdaeqaaOGaaiilaaaa@40BC@ соответственно, «мера инертности», «сила» и «энергия движения» системы по параметру x. Несложные преобразования последнего выражения приводят к нелинейному дифференциальному уравнению второго порядка (1) при λ=2, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaH7oaBcqGH9aqpcaaIYaGaaiil aaaa@4207@ α=2γ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGH9aqpcaaIYaGaeq4S dCgaaa@42E9@ и K=a m x γ1 . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbGaeyypa0Jaamyyaiaad2ga paWaaSbaaSqaa8qacaWG4baapaqabaGcdaahaaWcbeqaa8qacqaHZo WzcaaMc8UamyhGgkHiTiaaigdaaaGcpaGaaiOlaaaa@49D0@ В связи с вышесказанным на основе уравнения (1) представляется возможным предложить универсальную методику прогноза количественных характеристик саморазвивающихся природных процессов.

Для прогноза потенциально катастрофических процессов наиболее интересен случай x >> x 0 . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaacqGH+aGpcqGH+aGp ceWG4bGbauaapaWaaSbaaSqaa8qacaaIWaaapaqabaGccaGGUaaaaa@43D3@ Поэтому в качестве аппроксимационной модели имеет значение уравнение:

x =k x α . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaacqGH9aqpcaWGRbWd amaabmaabaWdbiqadIhagaqbaaWdaiaawIcacaGLPaaadaahaaWcbe qaa8qacqaHXoqyaaGccaGGUaaaaa@4638@ (2)

Решения уравнения (2) представимы в явном виде. При k=0 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyypa0JaaGimaaaa@4091@ они соответствуют линейным зависимостям: x= x 1 + x (t t 1 ), MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bGaeyypa0JaamiEa8aadaWg aaWcbaWdbiaaigdaa8aabeaak8qacqGHRaWkceWG4bGbauaacaGGOa GaamiDaiabgkHiTiaadshapaWaaSbaaSqaa8qacaaIXaaapaqabaGc peGaaiyka8aacaGGSaaaaa@4A21@ x =const. MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaacqGH9aqpcaqGJbGa ae4Baiaab6gacaqGZbGaaeiDaiaac6caaaa@4558@ При k0, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaiaacYca aaa@4202@ α1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGHGjsUcaaIXaaaaa@4202@ и α2: MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGHGjsUcaaIYaGaaiOo aaaa@42C1@ параболам (α<1), MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaeqySdeMaeyipaWJaaGym a8aacaGGPaGaaiilaaaa@4357@ гиперболам (1<α<2) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaaGymaiabgYda8iabeg7a HjabgYda8iaaikdapaGaaiykaaaa@4467@ и «супергиперболам» x= X a + [k(α1)( T a t)] ( a2)/(α1) / [k(2α)] , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bGaeyypa0ZaaSGbaeaacaWG ybWdamaaBaaaleaapeGaamyyaaWdaeqaaOGaaGjbV=qacWGtaA4kaS YdaiaacUfapeGaam4Aa8aacaGGOaWdbiabeg7aHjaaykW7caaMb8Ua mOiGgkHiTiaaysW7caaIXaWdaiaacMcacaGGOaWdbiaadsfapaWaaS baaSqaa8qacaWGHbaapaqabaGccaaMb8UaaGjbV=qacWGyaAOeI0Ia amiDa8aacaGGPaGaaiyxamacEcihaaWcbKGNagacEcOai4jGcIcaaa GcdGGNaYbaaSqaj4jGbGGNa+qacGGNaoyyaiacEciMc8Uam4jGgkHi TiacEciIYaWdaiacEcOGPaWdbiacEcOGVaWdaiacEcOGOaWdbiadEc iHXoqycWGNaAOeI0Iai4jGigdapaGai4jGcMcaaaGccaaMb8oapeqa a8aacaGGBbWdbiaadUgapaGaaiika8qacaaIYaGaaGjbVlaaygW7cq GHsislcqaHXoqypaGaaiykaiaac2faaaWdbiaacYcaaaa@89A5@ где T a = t 1 +( x 1 1α )/ [k(α1)] , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGubWdamaaBaaaleaapeGaamyy aaWdaeqaaOGaaGzaV=qacWGNaAypa0ZaaSGbaeaacaWG0bWdamaaBa aaleaapeGaaGymaaWdaeqaaOGaaGzaV=qacWaLaA4kaSYdaiaacIca peGabmiEayaafaWdamaaBaaaleaapeGaaGymaaWdaeqaaOWaaWbaaS qabeaapeGaiGkGigdacaaMi8UaaGPaVlabgkHiTiadOciHXoqyaaGc paGaaiykaaWdbeaapaGaai4wa8qacaWGRbGaaiikaiabeg7aHjadyb OHsislcaaMb8UaaGymaiaacMcapaGaaiyxaaaapeGaaiilaaaa@6101@ X a = x 1 +( x 1 2 α )/ [k(α2)] . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGybWdamaaBaaaleaapeGaamyy aaWdaeqaaOGaaGzaV=qacWGNaAypa0ZaaSGbaeaacaWG4bWdamaaBa aaleaapeGaaGymaaWdaeqaaOGaaGzaV=qacWaLaA4kaSYdaiaacIca peGabmiEayaafaWdamaaBaaaleaapeGaaGymaaWdaeqaaOWaiGkGCa aaleqcOcyaiGkGpeGaiGkGikdacWGXaAOeI0caaOWdamacOcihaaWc bKaQagacOc4dbiacOciMc8UamGkGeg7aHbaak8aacaGGPaaapeqaa8 aacaGGBbWdbiaadUgapaGaaiika8qacqaHXoqycaaMb8UamGkGgkHi TiaaikdapaGaaiykaiaac2faaaWdbiaac6caaaa@69DF@ При k0 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaaaa@4152@ и α=1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGH9aqpcaaIXaaaaa@4141@ решения представлены экспонентами: x= X a +( x 1 X a )exp[k(t t 1 )], MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bGaeyypa0Jaamiwa8aadaWg aaWcbaWdbiaadggaa8aabeaak8qacqGHRaWkpaGaaiika8qacaWG4b WdamaaBaaaleaapeGaaGymaaWdaeqaaOWdbiabgkHiTiaadIfapaWa aSbaaSqaa8qacaWGHbaapaqabaGccaGGPaWdbiaabwgacaqG4bGaae iCa8aacaGGBbWdbiaadUgapaGaaiika8qacaWG0bGaeyOeI0IaamiD a8aadaWgaaWcbaWdbiaaigdaa8aabeaakiaacMcacaGGDbGaaiilaa aa@5590@ где X a = x 1 x 1 /k . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGybWdamaaBaaaleaapeGaamyy aaWdaeqaaOGaaGzaV=qacWGNaAypa0ZaaSGbaeaacaWG4bWdamaaBa aaleaapeGaaGymaaWdaeqaaOGaaGzaV=qacWaLaAOeI0IabmiEayaa faWdamaaBaaaleaapeGaaGymaaWdaeqaaaGcpeqaaiaadUgaaaGaai Olaaaa@4D7D@ При k0 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaaaa@4152@ и α=2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGH9aqpcaaIYaaaaa@4142@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ логарифмическими зависимостями: x= x 1 +ln|( T a t 1 )/ ( T a t)| /k , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bGaaGzaVladYcOH9aqpdaWc gaqaamaalyaabaGaamiEa8aadaWgaaWcbaWdbiaaigdaa8aabeaaki aaygW7peGam4jGgUcaRiaabYgacaqGUbWdaiaacYhacaGGOaWdbiaa dsfapaWaaSbaaSqaa8qacaWGHbaapaqabaGccaaMb8+dbiaducOHsi slcaWG0bWdamaaBaaaleaapeGaaGymaaWdaeqaaOGaaiykaaWdbeaa paGaaiika8qacaWGubWdamaaBaaaleaapeGaamyyaaWdaeqaaOGaaG zaV=qacWGNaAOeI0IaamiDa8aacaGGPaGaaiiFaaaaa8qabaGaam4A aaaacaGGSaaaaa@5FD8@ где T a = t 1 +1/ (k x 1 ) . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGubWdamaaBaaaleaapeGaamyy aaWdaeqaaOWdbiabg2da9maalyaabaGaamiDa8aadaWgaaWcbaWdbi aaigdaa8aabeaak8qacWGyaA4kaSIaaGymaaqaa8aacaGGOaWdbiaa dUgacaaMi8UabmiEayaafaWdamaaBaaaleaapeGaaGymaaWdaeqaaO GaaiykaaaapeGaaiOlaaaa@4CC2@ В этих выражениях x 1 , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaajug5a8qa caaIXaaal8aabeaakiaacYcaaaa@420A@ x 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaapaWaaSbaaSqaa8qa caaIXaaapaqabaaaaa@3FFF@ и t 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaaGym aaWdaeqaaaaa@3FEF@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ начальные условия (значения параметра и скорости его изменения в определенные моменты времени), T a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGubWdamaaBaaaleaapeGaamyy aaWdaeqaaaaa@3FFA@ и X a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGybWdamaaBaaaleaapeGaamyy aaWdaeqaaaaa@3FFE@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ значения асимптот по времени и параметру. Следовательно, решения уравнения (2) представляют собой либо собственно линейную зависимость (k=0), MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaam4Aaiabg2da9iaaicda paGaaiykaiaacYcaaaa@42A9@ либо сводятся к линейным зависимостям при логарифмировании разностей между значениями параметра и/или времени и соответствующими асимптотами. При k0, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaiaacYca aaa@4202@ α1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGHGjsUcaaIXaaaaa@4202@ и α2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGHGjsUcaaIYaaaaa@4203@ решения имеют линейный вид в двойных логарифмических координатах: ln|x X a |=Aln|t T a |+B, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaqGSbGaaeOBa8aacaGG8bWdbiaa dIhacqGHsislcaWGybWdamaaBaaaleaapeGaamyyaaWdaeqaaOGaai iFa8qacqGH9aqpcaWGbbGaaeiBaiaab6gapaGaaiiFa8qacaWG0bGa eyOeI0Iaamiva8aadaWgaaWcbaWdbiaadggaa8aabeaakiaacYhape Gaey4kaSIaamOqaiaacYcaaaa@523E@ где A= (α2)/ (α1) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGbbGaeyypa0ZaaSGbaeaapaGa aiika8qacqaHXoqycqGHsislcaaIYaWdaiaacMcaa8qabaWdaiaacI capeGaeqySdeMaeyOeI0IaaGyma8aacaGGPaaaaaaa@4970@ и B= ln|k(α1)|×(α2)/ (α1)ln|k(α2)| . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGcbGaeyypa0ZaaSGbaeaacaqG SbGaaeOBa8aacaGG8bWdbiaadUgapaGaaiika8qacqaHXoqycqGHsi slcaaIXaWdaiaacMcacaGG8bWdbiadYcOHxdaTcaaMe8UaaGPaV=aa caGGOaWdbiabeg7aHjabgkHiTiaaikdapaGaaiykaaWdbeaapaGaai ika8qacqaHXoqycqGHsislcaaIXaWdaiaacMcapeGaeyOeI0IaaeiB aiaab6gapaGaaiiFa8qacaWGRbWdaiaacIcapeGaeqySdeMaeyOeI0 IaaGOma8aacaGGPaGaaiiFaaaapeGaaiOlaaaa@6524@ При k0 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaaaa@4152@ и α=1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGH9aqpcaaIXaaaaa@4141@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ линейный вид при логарифмировании логарифмических разностей по параметру ln|x X a |=At+B, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaqGSbGaaeOBa8aacaGG8bWdbiaa dIhacqGHsislcaWGybWdamaaBaaaleaapeGaamyyaaWdaeqaaOGaai iFa8qacWaQaAypa0JaamyqaiaadshacqGHRaWkcaWGcbGaaiilaaaa @4C4F@ где A=k MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGbbGaeyypa0Jaam4Aaaaa@409D@ и B=ln| x 1 X a |k× t 1 . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGcbGaeyypa0JaaeiBaiaab6ga paGaaiiFa8qacaWG4bWdamaaBaaaleaapeGaaGymaaWdaeqaaOWdbi abgkHiTiaadIfapaWaaSbaaSqaa8qacaWGHbaapaqabaGccaGG8bWd biabgkHiTiaaykW7caWGRbGaey41aqRaamiDa8aadaWgaaWcbaWdbi aaigdaa8aabeaakiaac6caaaa@5146@ При k0 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGRbGaeyiyIKRaaGimaaaa@4152@ и α=2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycqGH9aqpcaaIYaaaaa@4142@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ линейный вид при логарифмировании асимптотических разностей по времени x=A×ln| T a t|+B, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bGaeyypa0JaamyqaiabgEna 0kaabYgacaqGUbWdaiaacYhapeGaamiva8aadaWgaaWcbaWdbiaadg gaa8aabeaak8qacqGHsislcaWG0bWdaiaacYhapeGaey4kaSIaamOq aiaacYcaaaa@4D51@ где A= 1/k MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGbbGaeyypa0ZaaSGbaeaacqGH sislcaaIXaaabaGaam4Aaaaaaaa@425B@ и B= x 1 +ln| T a t 1 |/k . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGcbGaeyypa0ZaaSGbaeaacaWG 4bWdamaaBaaaleaapeGaaGymaaWdaeqaaOWdbiabgUcaRiaabYgaca qGUbWdaiaacYhapeGaamiva8aadaWgaaWcbaWdbiaadggaa8aabeaa k8qacqGHsislcaWG0bWdamaaBaaaleaapeGaaGymaaWdaeqaaOGaai iFaaWdbeaacaWGRbaaaiaac6caaaa@4DBB@

Линейность решений уравнения (2) в обычных или логарифмических координатах упрощает поиск наилучшего соответствия (оптимизацию) между частным решением уравнения (2) и аппроксимируемыми им фактическими данными. Прямая оптимизация решений уравнения (2) по пяти параметрам (показатель α, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycaGGSaaaaa@4030@ коэффициент k и начальные условия x 1 , x 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaapeGaaGym aaWdaeqaaOWdbiaacYcacaaMe8UaaGPaVlqadIhagaqba8aadaWgaa WcbaWdbiaaigdaa8aabeaaaaa@45F3@ и t 1 ) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaaGym aaWdaeqaaOGaaiykaaaa@40A6@ сложна и затратна по вычислительным ресурсам, но при использовании обычной или логарифмической линейности оптимизация сводится к рассмотрению и сопоставлению между собой нескольких вариантов линейной регрессии. При этом в некоторых вариантах требуется оптимизация по одному или двум дополнительным параметрам MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ асимптотам T a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGubWdamaaBaaaleaapeGaamyy aaWdaeqaaaaa@3FFA@ и/или X a . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGybWdamaaBaaaleaapeGaamyy aaWdaeqaaOWdbiaac6caaaa@40CA@ Оптимальные показатель α, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHXoqycaGGSaaaaa@4030@ коэффициент k и начальные условия x 1 , x 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaapeGaaGym aaWdaeqaaOWdbiaacYcacaaMe8UaaGPaVlqadIhagaqba8aadaWgaa WcbaWdbiaaigdaa8aabeaaaaa@45F3@ и t 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaaGym aaWdaeqaaaaa@3FEF@ для каждого варианта легко определяются аналитически по вышеприведенным формулам для констант линейности (A и B) и асимптот. Все это существенно упрощает процедуру оптимизации и снижает требования к вычислительным ресурсам.

Тем не менее, при сравнении вариантов линейной регрессии возникает проблема выбора критерия оптимизации MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ количественной характеристики соответствия между фактическими данными и аппроксимирующим их частным решением уравнения (2). Использование в качестве подобного критерия среднеквадратичного отклонения относительно линейных регрессий невозможно, так как в вариантах с логарифмическими координатами среднеквадратичное отклонение зависит от значений оптимизируемых асимптот. В частности, при использовании абсолютных величин отклонений в логарифмических координатах оптимальные значения асимптот уходят в бесконечность, в результате чего расстояния между точками (а следовательно, и среднеквадратичное отклонение) становятся бесконечно малыми. Использование относительных величин отклонений (относительно диапазона изменений логарифмов) приводит к обратной ситуации MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ в ходе оптимизационного поиска асимптоты максимально приближаются к краевым точкам аппроксимируемых данных, делая диапазон изменения логарифмов бесконечно большим, а величину относительных отклонений, соответственно, бесконечно малой. Поэтому все варианты линейной регрессии требуют сопоставления в обычных координатах. Однако и в этом случае поиск оптимального соответствия между решениями уравнения (2) и фактическими данными оказывается непростой задачей.

Здесь следует отметить, что уравнение (2) формально соответствует уравнению, предложенному Б. Войтом [Voight, 1988] для описания динамики хрупких разрушений в преддверии кульминации вулканических извержений. Уравнение Б. Войта используется в методе прогноза разрушений FFM (Forecasting Failure Method), однако в ряде современных работ [Bell et al., 2011; 2013; 2016] утверждается, что данный метод необъективен и неточен даже для ретроспективного анализа. Исходя из опыта автора этих строк, именно проблема с выбором критерия оптимизации стала причиной неудачи: стандартный метод наименьших квадратов, примененный исследователями, не обеспечивает устойчивости аппроксимационного моделирования и поэтому неэффективен.

Действительно, в случае резко нелинейных регрессионных зависимостей на участках с низкими скоростями изменения параметра, разброс его фактических значений много меньше, а по времени MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ много больше, чем на участках с высокими скоростями. Если использовать в качестве критерия оптимизации минимальность отклонений по параметру x, то аппроксимационная кривая будет подбираться так, чтобы лучше соответствовать участку с высокой активностью, тогда как небольшие отклонения на участке с низкой активностью в ходе оптимизации будут игнорироваться, и результирующая аппроксимационная кривая на этом участке пойдет с искажениями. При использовании в качестве критерия оптимизации отклонений по времени t ситуация сменится на противоположную MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ аппроксимационная кривая будет лучше всего оптимизирована на участке с низкими скоростями изменения параметра, тогда как на участках с высокими скоростями возможны искажения. Эти искажения тем выше, чем больше аппроксимируемая последовательность отличается от линейной зависимости, т. е. чем выше нелинейность исследуемого процесса.

Также не решают проблему аппроксимационных искажений попытки использования в качестве критерия оптимизации отклонений от нелинейной регрессии по нормали. В этом случае аппроксимационная кривая оптимизируется для максимального соответствия значениям параметра на участках с низкими скоростями его изменения, а на участках с высокими скоростями оптимизируется для соответствия значениям времени. Но одновременно при оптимизации игнорируется повышенный разброс данных по второй координате MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ по времени на участках с низкой активностью и по параметру на участках с высокой активностью.

Подобные искажения делают аппроксимационное моделирование неустойчивым, что, собственно, и предопределило приведенный выше вывод исследователей эффективности метода FFM. В результате искажений оптимальные параметры решений уравнения (2) становятся недостоверными и изменчивыми, что полностью исключает возможность их использования в прогнозных экстраполяциях. Тем не менее устранить искажения и повысить устойчивость аппроксимационного моделирования возможно, используя нестандартные критерии оптимизации [Малышев, 2005; Малышев, Тихонов, 2007]. В описываемой методике в этих целях используется среднеквадратичное бикоординатное отклонение Δ xt = {Σ(Δ x i ×Δ t i )/ [n×( x n x 1 )×( t n t 1 )] } 0.5 . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarpaWaaSbaaSqaa8qacaWG 4bGaamiDaaWdaeqaaOWdbiabg2da9maalyaabaWdaiaacUhapeGaeu 4Odm1daiaacIcapeGaeuiLdqKaaGjcVlaadIhapaWaaSbaaSqaa8qa caWGPbaapaqabaGcpeGaey41aqRaeuiLdqKaamiDa8aadaWgaaWcba WdbiaadMgaa8aabeaakiaacMcaa8qabaWdaiaacUfapeGaamOBaiab gEna0+aacaGGOaWdbiaadIhapaWaaSbaaSqaa8qacaWGUbaapaqaba GcpeGaeyOeI0IaamiEa8aadaWgaaWcbaWdbiaaigdaa8aabeaakiaa cMcapeGaey41aq7daiaacIcapeGaamiDa8aadaWgaaWcbaWdbiaad6 gaa8aabeaak8qacqGHsislcaWG0bWdamaaBaaaleaapeGaaGymaaWd aeqaaOGaaiykaiaac2facaGG9bWaaWbaaSqabeaapeGaaGimaiaac6 cacaaI1aaaaaaakiaac6caaaa@6B0C@ Здесь: n MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ число точек на аппроксимируемом участке фактических данных; ( x n x 1 ) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaamiEa8aadaWgaaWcbaWd biaad6gaa8aabeaak8qacqGHsislcaWG4bWdamaaBaaaleaapeGaaG ymaaWdaeqaaOGaaiykaaaa@44A7@ и ( t n t 1 ) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaamiDa8aadaWgaaWcbaWd biaad6gaa8aabeaak8qacqGHsislcaWG0bWdamaaBaaaleaapeGaaG ymaaWdaeqaaOGaaiykaaaa@449F@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ диапазоны изменения фактических данных на этом участке по параметру x и времени t, соответственно, (выполняют функции нормирования обеих координат на диапазон изменений от 0 до 1); Δ x i MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarcaaMi8UaamiEa8aadaWg aaWcbaWdbiaadMgaa8aabeaaaaa@431D@ и Δ t i MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarcaaMi8UaamiDa8aadaWg aaWcbaWdbiaadMgaa8aabeaaaaa@4319@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ отклонения каждой точки фактических данных от расчетной кривой по оси абсцисс и по оси ординат, соответственно. В геометрическом смысле бикоординатное отклонение каждой фактической точки соответствует стороне квадрата, равного по площади прямоугольнику со сторонами Δ x i MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarcaaMi8UaamiEa8aadaWg aaWcbaWdbiaadMgaa8aabeaaaaa@431D@ и Δ t i , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarcaaMi8UaamiDa8aadaWg aaWcbaWdbiaadMgaa8aabeaakiaacYcaaaa@43D3@ т. е. оно является средним геометрическим этих отклонений. Для повышения чувствительности оптимизационный поиск осуществляется по максимуму обратной величины MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ коэффициента упорядоченности K reg =1/ Δ xt . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbWdamaaBaaaleaacaWGYbGa amyzaiaadEgaaeqaaOWdbiabg2da9maalyaabaGaaGymaaqaaiabfs 5ae9aadaWgaaWcbaWdbiaadIhacaWG0baapaqabaaaaOWdbiaac6ca aaa@482C@ В приведенных ниже таблицах для характеристики качества аппроксимации также используется уровень упорядоченности L reg =lg( K reg ). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGmbWdamaaBaaaleaapeGaamOC aiaadwgacaWGNbaapaqabaGcpeGaeyypa0JaaeiBaiaabEgapaGaai ika8qacaWGlbWdamaaBaaaleaapeGaamOCaiaadwgacaWGNbaapaqa baGccaGGPaWdbiaac6caaaa@4B0D@

В ретроспективных исследованиях прогнозируемости каждое событие анализируемого каталога последовательно рассматривается как «текущее» событие. Момент времени этого события принимается за «настоящее». Время, предшествовавшее данному событию, считается «прошлым», а последующее время MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ «будущим». В окрестностях гипоцентра текущего события формируется выборка землетрясений с заданным радиусом захвата. Опорный участок для прогнозных экстраполяций выбирается при помощи пробных аппроксимаций. Первая пробная аппроксимация включает минимальное число событий MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 7, к каждой последующей добавляется ближайшее событие из «прошлого» вплоть до включения первого события в выборке. Все аппроксимации с K reg <10 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbWdamaaBaaaleaapeGaamOC aiaadwgacaWGNbaapaqabaGcpeGaeyipaWJaaGymaiaaicdaaaa@446B@ игнорируются. Из числа пробных аппроксимаций для ретропрогнозных оценок выбираются пять вариантов: первый MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ по максимуму коэффициента упорядоченности K reg , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbWdamaaBaaaleaapeGaamOC aiaadwgacaWGNbaapaqabaGccaGGSaaaaa@4292@ остальные MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ по ближайшему и главному максимумам нелинейности как для активизации (k>0), MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaam4Aaiabg6da+iaaicda paGaaiykaiaacYcaaaa@42AB@ так и для затухания (k<0). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaam4AaiabgYda8iaaicda paGaaiykaiaac6caaaa@42A9@ В качестве критерия нелинейности используется соотношение K reg / K lin , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaWaaSGbaeaaqaaaaaaaaaWdbiaadUeapaWaaSbaaSqa aiaadkhacaWGLbGaam4zaaqabaaakeaapeGaam4sa8aadaWgaaWcba GaamiBaiaadMgacaWGUbaabeaaaaGccaGGSaaaaa@4680@ где K lin MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbWdamaaBaaaleaacaWGSbGa amyAaiaad6gaaeqaaaaa@41BE@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ упорядоченность рассматриваемого участка в случае линейной аппроксимации. Первый вариант определяется всегда, остальные MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ в зависимости от наличия и сочетания текущих тенденций нелинейности процесса. Варианты нелинейности позволяют отслеживать на фоне главных тенденций начинающиеся (и поэтому пока еще слабо выраженные) новые тенденции развития.

Под прогнозируемостью здесь и далее понимается нахождение фактических данных «будущего» в полосе допустимых ошибок относительно расчетной кривой в ее экстраполяционной части. Для оценки прогнозируемости используется среднее отклонение от фактических точек от расчетной кривой по нормали в координатах, нормированных на диапазон от 0 до 1. Затем аппроксимация экстраполируется в «будущее» до тех пор, пока нормальное расстояние каждой последующей (прогнозируемой) фактической точки до расчетной кривой находится в полосе допустимых ошибок (±3σ). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaeyySaeRaaG4maiabeo8a Z9aacaGGPaGaaiOlaaaa@4469@

Количественная оценка дальности прогноза определяется через величину прогнозной дистанции Δ= { [( t p t n )/( t n t 1 )] 2 + [( x p x n )/( x n x 1 )] 2 } 0.5 , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarcqGH9aqppaGaai4Eaiaa cUfacaGGOaWdbiaadshapaWaaSbaaSqaa8qacaWGWbaapaqabaGcpe GaeyOeI0IaamiDa8aadaWgaaWcbaWdbiaad6gaa8aabeaakiaacMca peGaai4laiaacIcacaWG0bWdamaaBaaaleaapeGaamOBaaWdaeqaaO WdbiabgkHiTiaadshapaWaaSbaaSqaa8qacaaIXaaapaqabaGcpeGa aiykaiaac2fadaahaaWcbeqaaiaaikdaaaGccqGHRaWkcaGGBbWdai aacIcapeGaamiEa8aadaWgaaWcbaWdbiaadchaa8aabeaak8qacqGH sislcaWG4bWdamaaBaaaleaapeGaamOBaaWdaeqaaOGaaiyka8qaca GGVaGaaiikaiaadIhapaWaaSbaaSqaa8qacaWGUbaapaqabaGcpeGa eyOeI0IaamiEa8aadaWgaaWcbaWdbiaaigdaa8aabeaak8qacaGGPa Wdaiaac2fadaahaaWcbeqaa8qacaaIYaaaaOWdaiaac2hadaahaaWc beqaa8qacaaIWaGaaiOlaiaaiwdaaaGcpaGaaiilaaaa@6954@ где: x p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaapeGaamiC aaWdaeqaaaaa@402D@ и t p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaiiMD dchaa8aabeaaaaa@4109@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ значения параметра и времени предельного прогнозируемого события x n MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaapeGaamOB aaWdaeqaaaaa@402B@ и t n MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaamOB aaWdaeqaaaaa@4027@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ соответствующие значения для «текущего» события и x 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG4bWdamaaBaaaleaapeGaaGym aaWdaeqaaaaa@3FF3@ и t 1 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWG0bWdamaaBaaaleaapeGaaGym aaWdaeqaaaaa@3FEF@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ для начального события в опорной (для аппроксимации и последующего прогноза) последовательности. Проекции прогнозной дистанции Δ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoaraaa@3F47@ на оси координат характеризуют дальность прогноза (прогнозные дистанции) по времени Δ t MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarpaWaaSbaaSqaa8qacaWG 0baapaqabaaaaa@409A@ и параметру Δ x . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarpaWaaSbaaSqaa8qacaWG 4baapaqabaGccaGGUaaaaa@415A@ Для оценки качества прогноза используется относительная прогнозная дистанция Δ rel =Δ/σ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarpaWaaSbaaSqaa8qacaWG YbGaamyzaiaadYgaa8aabeaak8qacqGH9aqpdaWcgaqaaiabfs5aeb qaaiabeo8aZbaaaaa@46D2@ или ее десятичный логарифм MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ уровень прогнозируемости L p =lg( Δ rel ). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGmbWdamaaBaaaleaapeGaamiC aaWdaeqaaOWdbiabg2da9iaabYgacaqGNbWdaiaacIcapeGaeuiLdq 0damaaBaaaleaapeGaamOCaiaadwgacaWGSbaapaqabaGccaGGPaWd biaac6caaaa@49D0@

Для дифференцированной оценки прогнозной статистики по активизации и затуханию, а также для определения важных для прогноза значений показателя степени нелинейности α MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaeqySdegaaa@3F60@ в уравнениях (1) и (2) используется коэффициент прогнозной нелинейности K pn = Δ rel ×lg x p / x n , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbWdamaaBaaaleaapeGaamiC aiaad6gaa8aabeaak8qacqGH9aqpcqqHuoarpaWaaSbaaSqaa8qaca WGYbGaamyzaiaadYgaa8aabeaak8qacqGHxdaTcaqGSbGaae4za8aa daabdaqaa8qadaWcgaqaaiqadIhagaqba8aadaWgaaWcbaWdbiaadc haa8aabeaaaOWdbeaaceWG4bGbauaapaWaaSbaaSqaa8qacaWGUbaa paqabaaaaaGccaGLhWUaayjcSdGaaiilaaaa@5388@ где x p = x t n + t p /2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaapaWaaSbaaSqaa8qa caWGWbaapaqabaGcpeGaeyypa0JabmiEayaafaWdamaabmaabaWaaS Gbaeaadaqadaqaa8qacaWG0bWdamaaBaaaleaapeGaamOBaaWdaeqa aOWdbiabgUcaRiaadshapaWaaSbaaSqaa8qacaWGWbaapaqabaaaki aawIcacaGLPaaaaeaapeGaaGOmaaaaa8aacaGLOaGaayzkaaaaaa@4C18@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ прогнозируемая на середину прогнозного интервала скорость изменения параметра, а x n = x t n MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qaceWG4bGbauaapaWaaSbaaSqaa8qa caWGUbaapaqabaGcpeGaeyypa0JabmiEayaafaWdamaabmaabaWdbi aadshapaWaaSbaaSqaa8qacaWGUbaapaqabaaakiaawIcacaGLPaaa aaa@4658@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ ее текущее значение. Более подробно методика оценки прогнозируемости изложена в работе [Малышев, 2016].

При пространственном анализе сейсмических данных оценка прогнозируемости осуществляется по фиксированным сферическим гипоцентральным выборкам с радиусами 1.5, 3, 7.5, 15, 30, 60 и 150 км. Выборки распределены по широте, долготе и глубине с шагом смещения, в 1.5 раза меньшим радиуса выборки (т. е., соответственно, 1, 2, 5, 10, 20, 40 и 100 км), что обеспечивает пространственное перекрытие выборок и исключает пропуск данных для прогностических оценок.

Ради определенности под сильными землетрясениями понимаются такие землетрясения, которые в кумулятивном распределении по энергии превышают порог 99.9% от общего числа землетрясений. В связи с различиями в регистрируемости сейсмического потока в разных районах земного шара данное определение применяется по фиксированным сферическим гипоцентральным выборкам с радиусом 100 км, в которых зарегистрировано более 1000 землетрясений. В том случае, если в выборке зарегистрировано от 100 до 1000 землетрясений, под сильным землетрясением понимается самое сильное землетрясение выборки. В выборках со слабой (от 10 до 100) и очень слабой (менее 10 землетрясений) регистрируемости сейсмического потока землетрясений сильные землетрясения в составе выборок не выделяются.

ИСХОДНЫЕ ДАННЫЕ

В качестве исходных данных в работе используется Всемирный каталог Геологической службы США по состоянию на 1 января 2017 г.[1] Прогнозируемость потока сейсмической энергии Северной Америки изучалась в пределах координат 30° MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 75° по широте, 170° MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 180° и MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 180° MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ ( MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 70°) по долготе при глубине от MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 4.9 до 300.0 км. В рассматриваемых пределах расположены гипоцентры 1 514 937 землетрясений с магнитудой M=1.0+9.2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGnbGaeyypa0JaeyOeI0IaaGym aiaac6cacaaIWaGaeyOjGWRaey4kaSIaaGyoaiaac6caju2xbiaaik daaaa@483C@ при ее среднем значении 1.5. В соответствии с приведенным выше определением в числе этих землетрясений выделяются 1422 сильных толчка с M=2.99.2 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGnbGaeyypa0JaaGOmaiaac6ca caaI5aGaeyOeI0IaaGyoaiaac6cacaaIYaaaaa@4508@ (в среднем 5.1). В качестве параметра x рассматривается сумма энергии землетрясений E. При этом энергия одиночного землетрясения оценивается согласно имеющейся зависимости между его магнитудой M и энергетическим классом K [Kanamori, 1977]: K=1.5×M+4.8. MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGlbGaeyypa0JaaGymaiaac6ca caaI1aGaey41aqRaamytaiabgUcaRiaaisdacaGGUaGaaGioaiaac6 caaaa@4892@

РЕЗУЛЬТАТЫ ИССЛЕДОВАНИЙ И ИХ ОБСУЖДЕНИЕ

Сводная статистика ретропрогнозных оценок приведена в табл. 1. В большинстве прогнозных определений (73.9%) прогнозная дистанция Δ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoaraaa@3F47@ более чем в 3 раза превышает величину средней ошибки σ, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHdpWCcaGGSaaaaa@4054@ т. е. подобные прогнозные определения рассматриваются как значимые. Максимальные уровни прогнозируемости L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacaWGmbWdamaaBaaaleaapeGaamiC aaWdaeqaaaaa@4001@ соответствуют превышению прогнозной дистанции Δ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoaraaa@3F47@ над средним отклонением σ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHdpWCaaa@3FA4@ на 6.0 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 8.6 порядка, причем максимальная прогнозируемость потока сейсмической энергии отмечается на малых гипоцентральных радиусах выборок (1.5 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 3 км). Средние уровни прогнозируемости соответствуют превышению прогнозной дистанции Δ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoaraaa@3F47@ над средним отклонением σ MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqaHdpWCaaa@3FA4@ на 1.4 порядка. Средневзвешенные значения прогнозных дистанций по времени Δ t MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaaeaaaaaaaaa8qacqqHuoarpaWaaSbaaSqaa8qacaWG 0baapaqabaaaaa@409A@ составляют от нескольких дней до нескольких месяцев для активизации сейсмичности и несколько лет для ее затухания.

На рис. 1 отображены значения прогнозной нелинейности[2] для всех определений, у которых K pn > 1, MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaWaaqWaaeaaqaaaaaaaaaWdbiaadUeapaWaaSbaaSqa a8qacaWGWbGaamOBaaWdaeqaaaGccaGLhWUaayjcSdWdbiabg6da+i aabccacaaIXaGaaiilaaaa@4745@ а также отображены экстремумы прогнозной нелинейности, связанные с сильными землетрясениями. Как можно видеть, экстремумы прогнозной нелинейности, свойственные сильным землетрясениям, как правило, соответствуют аналогичным экстремумам сейсмического потока в целом.

Статистические оценки прогнозно значимого показателя степени α демонстрируют (см. табл. 1 и рис. 2), что нелинейность как активизации сейсмического процесса, так и его затухания, определяется классом гиперболических функций (1<α<2). MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaaGymaiabgYda8iabeg7a HjabgYda8KqzFfGaaGOmaOWdaiaacMcacaGGUaaaaa@45F1@ Однако достаточно большой разброс значений показателя α не позволяет ограничиться равнобокой гиперболой (α=1.5) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaeqySdeMaeyypa0JaaGym aiaac6cacaaI1aWdaiaacMcaaaa@441A@ в качестве математической модели для ретропрогнозных оценок.

 

Таблица 1. Статистика ретропрогнозов потока сейсмической энергии Северной Америки в 1900 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzafaeaaaaaaaaa8qacaWFtacaaa@3983@ 2016 гг.

Радиус, км

 

Число определений

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaWaaeqabaabae aafaaakeaajugqbabaaaaaaaaapeGaamitaOWdamaaBaaaleaapeGa amiCaaWdaeqaaaaa@3DA1@

 

Δ t , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciGacaWaaeqabaabae aafaaakeaajugqbabaaaaaaaaapeGaeuiLdqKcpaWaaSbaaSqaa8qa caWG0baapaqabaGcpeGaaiilaaaa@3F04@ сут*

 

lg( Δ t / σ t )** MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaajugqbabaaaaaaaaapeGaaeiBaiaabEgak8aacaGGOaWa aSGbaeaapeGaeuiLdq0damaaBaaaleaapeGaamiDaaWdaeqaaaGcba Wdbiabeo8aZ9aadaWgaaWcbaWdbiaadshaa8aabeaaaaGccaGGPaWd biaacQcacGGyakOkaaaa@472F@

 

lg( Δ x / σ x )** MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaajugqbabaaaaaaaaapeGaaeiBaiaabEgak8aacaGGOaWa aSGbaeaajugqb8qacqqHuoark8aadaWgaaWcbaWdbiaadIhaa8aabe aaaOqaa8qacqaHdpWCpaWaaSbaaSqaa8qacaWG4baapaqabaaaaOGa aiyka8qacaGGQaGaiWgGcQcaaaa@47FA@

 

α* MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHjacSbOGQaaaaa@3E07@

 

всего

 

значимых

 

активизация

 

затухание

 

макс.

 

средний

 

активизация

 

затухание

 

активизация

 

затухание

 

активизация

 

затухание

 

активизация

 

затухание

 

1.5

 

1858728

 

1332107

 

542554

 

774714

 

8.2751

 

1.3502

 

10.39

 

883.6

 

0.3031

 

4.1859

 

3.6329

 

0.0422

 

1.4758

 

1.7864

 

3

 

2561277

 

1883261

 

763171

 

1100550

 

8.6306

 

1.3816

 

4.741

 

929.2

 

0.3525

 

4.4457

 

3.5743

 

0.0589

 

1.5028

 

1.7719

 

7.5

 

3196678

 

2373744

 

955134

 

1398351

 

7.3120

 

1.3713

 

51.49

 

890.3

 

0.4045

 

4.5929

 

3.2394

 

0.0493

 

1.4582

 

1.7613

 

15

 

3371016

 

2503063

 

956001

 

1526345

 

7.3299

 

1.3706

 

57.81

 

868.2

 

0.4260

 

4.7022

 

3.0017

 

0.0338

 

1.4634

 

1.7429

 

30

 

3438244

 

2551777

 

928634

 

1600794

 

6.7195

 

1.3615

 

64.38

 

741.6

 

0.4421

 

4.7295

 

2.6949

 

0.0480

 

1.4782

 

1.7444

 

60

 

3279054

 

2433215

 

853445

 

1553910

 

7.2855

 

1.3915

 

187.6

 

693.4

 

0.4559

 

4.8113

 

2.4340

 

0.0502

 

1.5011

 

1.7370

 

150

 

2784275

 

2063840

 

660428

 

1387782

 

5.9819

 

1.4477

 

217.5

 

741.5

 

0.4590

 

4.8933

 

2.2879

 

0.0218

 

1.4869

 

1.7108

 

Все

 

20489272

 

15141007

 

5659367

 

9342446

 

8.6306

 

1.3826

 

14.47

 

810.8

 

0.4105

 

4.6660

 

2.9697

 

0.0431

 

1.4901

 

1.7473

 

Примечание: * MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса модуля коэффициента прогнозной нелинейности K pn ; MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaadaabdaqaaabaaaaaaaaapeGaam4sa8aadaWgaaWcbaWd biaadchacaWGUbaapaqabaaakiaawEa7caGLiWoacaGG7aaaaa@4444@ ** MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса десятичного логарифма отношения прогнозной скорости x p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiqadIhagaqba8aadaWgaaWcbaWdbiaa dchaa8aabeaaaaa@3F9F@ к текущей x c . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiqadIhagaqba8aadaWgaaWcbaWdbiaa dogaa8aabeaak8qacaGGUaaaaa@405E@

 

Рис. 1. Прогнозируемость потока сейсмической энергии и сильных землетрясений Северной Америки в 1962–2016 гг. Круги соответствуют экстремумам прогнозной нелинейности сильных землетрясений. Верхняя половина диаграммы характеризует прогнозы на активизацию сейсмического потока и форшоковую прогнозируемость сильных землетрясений, нижняя – прогнозы на снижение сейсмической активности и афтершоковую прогнозируемость. Нумерация сильных землетрясений в верхней части диаграммы соответствует табл. 4, табл. 6 и рис. 3; в нижней части диаграммы – табл. 5 и табл. 7.

 

Рис. 2. Прогнозная значимость показателя степени нелинейности α. См. примечание к рис. 1.

 

В табл. 2 приведена общая статистика ретропрогнозов сильных землетрясений Северной Америки по потоку сейсмической энергии. Форшоковая прогнозируемость (хотя бы однократное попадание «будущего» сильного землетрясения в полосу допустимых ошибок относительно расчетной кривой в ее экстраполяционной части) фиксируется для 1120 из 1422 сильных землетрясений региона. Она характеризуется почти 215 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaacdaaeaaaaaaaaa8qacqWF8iIFcaaIYaGaaGymaiaa iwdaaaa@4183@ тысячами ретропрогнозных определений, для которых сильное землетрясение оказывается в полосе ошибок (±3σ) MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacHOaM0xg9vrFfpeea0xh9v8 qiW7rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpe pae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGacaGaamaabeqaaq aabaqbaaGcbaGaaiikaabaaaaaaaaapeGaeyySaeRaaG4maiabeo8a Z9aacaGGPaaaaa@43B7@ экстраполяционной части прогнозной зависимости (рис. 3). Форшоковая прогнозируемость сильных землетрясений по потоку сейсмической энергии начинает проявляться в количестве прогнозируемых землетрясений на малых (1.5 и 3 км) радиусах гипоцентральных выборок, с последующим быстрым возрастанием на средних (от 7.5 до 30 км) радиусах, а затем более плавно продолжает увеличиваться на больших (60 и 150 км) радиусах. На малых гипоцентральных радиусах отмечаются в среднем более высокие уровни прогнозируемости и прогнозной нелинейности. Средняя прогнозная дистанция по времени в форшоковой прогнозируемости меняется от нескольких дней на малых радиусах до нескольких месяцев на средних радиусах и превышает полгода на больших радиусах.

 

Таблица 2. Статистика ретропрогнозов сильных землетрясений Северной Америки в 1900 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzafaeaaaaaaaaa8qacaWFtacaaa@3983@ 2016 гг.

Радиус, км

 

Кол-во сильных землетрясений, имеющих форшоковую прогнозируемость

 

Кол-во форшоковых ретропрогнозных определений

 

Средняя прогнозная дистанция по времени, сут*

 

lg K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaabYgacaqGNbWaaqWaaeaacaWGlbWd amaaBaaaleaapeGaamiCaiaad6gaa8aabeaaaOWdbiaawEa7caGLiW oaaaa@42ED@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE6@

 

α* MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHjacIbOGQaaaaa@3DFD@

 

макс.

 

средн.

 

макс.

 

средн.

 

1.5

 

211

 

4902

 

7.937

 

8.041

 

1.732

 

8.275

 

2.201

 

1.482

 

3

 

400

 

18651

 

2.349

 

8.344

 

1.616

 

8.631

 

2.134

 

1.508

 

7.5

 

647

 

48149

 

48.85

 

6.668

 

1.432

 

5.888

 

2.031

 

1.485

 

15

 

753

 

52532

 

82.57

 

5.664

 

1.305

 

5.784

 

1.914

 

1.486

 

30

 

830

 

36031

 

79.73

 

5.577

 

1.404

 

5.444

 

1.909

 

1.483

 

60

 

872

 

28953

 

256.3

 

5.342

 

1.429

 

5.378

 

1.891

 

1.509

 

150

 

892

 

25505

 

323.3

 

4.474

 

1.394

 

4.969

 

1.862

 

1.532

 

Все

 

1120

 

214723

 

10.56

 

8.344

 

1.414

 

8.631

 

1.956

 

1.498

 

Примечание: * MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса модуля коэффициента прогнозной нелинейности K pn . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaadaabdaqaaabaaaaaaaaapeGaam4sa8aadaWgaaWcbaWd biaadchacaWGUbaapaqabaaakiaawEa7caGLiWoapeGaaiOlaaaa@4447@

 

Таблица 3. Статистика ретропрогнозов затухания сейсмичности после сильных землетрясений Северной Америки в 1900 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzafaeaaaaaaaaa8qacaWFtacaaa@3983@ 2016 гг.

Радиус, км

 

Кол-во сильных землетрясений с прогнозируемым затуханием сейсмичности

 

Кол-во афтершоковых ретропрогнозных определений

 

Средняя прогнозная дистанция по времени, сут*

 

lg K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaabYgacaqGNbWaaqWaaeaacaWGlbWd amaaBaaaleaapeGaamiCaiaad6gaa8aabeaaaOWdbiaawEa7caGLiW oaaaa@42ED@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE6@

 

α* MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHjacSbOGQaaaaa@3E07@

 

макс.

 

средн.

 

макс.

 

средн.

 

1.5

 

573

 

71534

 

6611

 

7.811

 

2.066

 

7.103

 

2.490

 

1.654

 

3

 

861

 

185394

 

5671

 

8.101

 

2.055

 

7.428

 

2.482

 

1.647

 

7.5

 

1097

 

402312

 

5768

 

8.086

 

1.890

 

7.312

 

2.344

 

1.642

 

15

 

1210

 

529754

 

6319

 

7.986

 

1.815

 

7.330

 

2.291

 

1.671

 

30

 

1327

 

607465

 

1907

 

7.248

 

1.759

 

6.720

 

2.254

 

1.671

 

60

 

1362

 

651773

 

2320

 

6.843

 

1.736

 

6.424

 

2.258

 

1.703

 

150

 

1378

 

646558

 

593.4

 

6.292

 

1.660

 

5.707

 

2.203

 

1.644

 

Все

 

1410

 

3094790

 

5390

 

8.101

 

1.785

 

7.428

 

2.281

 

1.658

 

Примечание: * MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса модуля коэффициента прогнозной нелинейности K pn . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaadaabdaqaaabaaaaaaaaapeGaam4sa8aadaWgaaWcbaWd biaadchacaWGUbaapaqabaaakiaawEa7caGLiWoapeGaaiOlaaaa@4447@

 

Статистика ретропрогнозов затухания сейсмичности после сильных землетрясений приведена в табл. 3. Афтершоковая прогнозируемость по выделяющейся сейсмической энергии прослеживается для 1410 из 1422 сильных землетрясений и характеризуется 3 млн ретропрогнозных определений, что на порядок больше по сравнению с форшоковой прогнозируемостью. Афтершоковая прогнозируемость затухания сейсмичности после сильных толчков появляется и быстро нарастает на малых (1.5 и 3 км) радиусах гипоцентральных выборок, а затем более плавно увеличивается на средних (от 7.5 до 30 км) и больших (60 и 150 км) радиусах. Наиболее высокие уровни прогнозируемости и прогнозной нелинейности отмечаются для выборок с гипоцентральным радиусом 3 км, тогда как по мере увеличения радиусов прослеживается тенденция к уменьшению уровней прогнозируемости и прогнозной нелинейности. Средняя прогнозная дистанция по времени в афтершоковой прогнозируемости более чем на два порядка выше аналогичного параметра форшоковой прогнозируемости, на радиусах 1.5 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 15 км она превышает 10 лет, а при дальнейшем увеличении радиуса гипоцентральных выборок снижается до 1.5 лет.

Табл. 4 и табл. 5 содержат сведения по статистике, соответственно, форшоковой и афтершоковой прогнозируемости некоторых сильных землетрясений Северной Америки по потоку сейсмической энергии. Табл. 6 и табл. 7 содержат характеристики ретропрогнозных зависимостей с экстремальной прогнозной нелинейностью соответствующих землетрясений из табл. 4 и табл. 5. Рис. 4 иллюстрирует пространственное распределение сильных землетрясений Северной Америки и их форшоковую и афтершоковую прогнозируемость.

 

Рис. 3. Графики ретропрогнозных определений, соответствующих максимумам нелинейной прогнозируемости некоторых сильных землетрясений: 1 – кривая фактических данных, 2 – расчетная кривая, 3 – полоса ошибок (±3σ) 4 – момент ретропрогноза, 5 – сильное землетрясение. Порядковые номера графиков соответствуют нумерации в табл. 4 и табл. 6. Графики слева характеризуют аппроксимационные части прогнозных определений, справа – прогнозные зависимости в целом. Пересечение точечных вертикальных и горизонтальных линий на графиках соответствует «текущим» значениям времени и параметра, левее и ниже этого пересечения – «прошлое», правее и выше – «будущее». Пунктирными линиями показано положение асимптот Ta и Xa

 

Таблица 4. Прогнозируемость некоторых сильных землетрясений Северной Америки в 1900 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzafaeaaaaaaaaa8qacaWFtacaaa@3983@ 2016 гг.

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFwecaaa@3967@ п. п.

 

Землетрясение

 

Статистика прогнозируемости

 

Время

 

K

 

Гипоцентр

 

Кол-во определений

 

Дистанция по времени**, сут

 

lg K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaabYgacaqGNbWaaqWaaeaacaWGlbWd amaaBaaaleaapeGaamiCaiaad6gaa8aabeaaaOWdbiaawEa7caGLiW oaaaa@42ED@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE6@

 

α* MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHjacSbOGQaaaaa@3E07@

 

широта

 

долгота

 

глубина

 

средн.*

 

на максимуме K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadUeapaWaaSbaaSqaa8qacaWGWbGa amOBaaWdaeqaaaaa@3DD8@

 

макс.

 

средн.

 

макс.

 

средн.

 

1

 

1934.06.08 04:47:46

 

13.6

 

35.846

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.666

 

6.0

 

14

 

1.403

 

1.255

 

3.531

 

2.794

 

3.533

 

3.050

 

1.540

 

2

 

1937.09.01 13:48:09

 

11.4

 

34.181

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.557

 

0.3

 

2

 

10.02

 

0.580

 

3.343

 

2.655

 

3.136

 

2.618

 

1.280

 

3

 

1940.05.19 04:36:41

 

15.2

 

32.844

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.381

 

6.0

 

17

 

127.5

 

0.091

 

3.481

 

2.521

 

3.935

 

2.729

 

1.619

 

4

 

1947.04.11 07:47:09

 

12.3

 

34.959

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.526

 

6.0

 

16

 

0.123

 

0.016

 

4.578

 

3.082

 

4.431

 

3.336

 

1.264

 

5

 

1952.07.25 19:43:24

 

13.2

 

35.304

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.468

 

6.0

 

31

 

3.427

 

3.855

 

4.424

 

2.751

 

4.113

 

2.966

 

1.494

 

6

 

1956.03.16 20:29:34

 

11.9

 

34.289

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.775

 

2.7

 

13

 

6.545

 

0.032

 

2.750

 

1.306

 

3.272

 

1.888

 

1.827

 

7

 

1962.12.02 00:41:40

 

11.5

 

34.301

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.886

 

6.0

 

6

 

17.85

 

19.36

 

3.377

 

2.373

 

3.325

 

2.729

 

1.322

 

8

 

1965.09.25 17:43:44

 

12.5

 

34.714

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.432

 

6.0

 

20

 

43.39

 

15.12

 

3.184

 

0.488

 

3.706

 

1.369

 

1.985

 

9

 

1970.09.12 14:30:53

 

12.6

 

34.255

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.534

 

10.8

 

11

 

65.92

 

0.014

 

3.037

 

0.792

 

3.558

 

1.650

 

1.950

 

10

 

1975.06.01 01:38:48

 

12.7

 

34.512

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.488

 

0.1

 

101

 

12.66

 

0.002

 

4.263

 

1.506

 

4.685

 

1.976

 

1.837

 

11

 

1978.03.11 23:57:51

 

11.9

 

32.601

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.294

 

10.0

 

49

 

30.91

 

44.46

 

3.840

 

1.176

 

3.407

 

1.640

 

1.473

 

12

 

1980.05.25 19:44:50

 

14.5

 

37.696

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.750

 

6.0

 

328

 

25.82

 

0.063

 

5.949

 

2.888

 

5.319

 

3.231

 

1.516

 

13

 

1982.10.01 14:29:01

 

12.5

 

35.743

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.756

 

3.0

 

2351

 

66.11

 

112.6

 

3.759

 

1.663

 

3.457

 

2.035

 

1.554

 

14

 

1984.11.23 19:12:34

 

13.1

 

37.432

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.607

 

10.5

 

8

 

0.194

 

0.010

 

6.595

 

3.861

 

5.870

 

4.048

 

1.497

 

15

 

1987.11.24 13:15:56

 

14.6

 

33.010

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.850

 

1.0

 

170

 

0.028

 

0.022

 

8.072

 

3.177

 

7.155

 

3.449

 

1.492

 

16

 

1990.02.28 23:43:36

 

13.4

 

34.140

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.690

 

10.0

 

67

 

284.9

 

359.8

 

4.097

 

2.738

 

3.673

 

2.932

 

1.465

 

17

 

1992.06.28 11:57:34

 

15.8

 

34.200

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.437

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 0.1

 

2583

 

1.159

 

0.042

 

8.344

 

2.908

 

8.631

 

3.127

 

1.556

 

18

 

1995.09.20 23:27:36

 

13.4

 

35.761

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.638

 

4.7

 

4892

 

9.221

 

7.221

 

7.788

 

2.266

 

6.905

 

2.466

 

1.468

 

19

 

1999.10.21 01:54:06

 

12.3

 

34.867

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.393

 

3.1

 

706

 

0.908

 

0.396

 

6.043

 

2.648

 

5.509

 

2.847

 

1.419

 

20

 

2002.11.03 22:12:41

 

16.7

 

63.517

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 147.444

 

4.9

 

9

 

11.66

 

10.85

 

5.351

 

4.363

 

4.889

 

4.260

 

1.435

 

21

 

2005.09.02 01:27:19

 

12.5

 

33.153

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.646

 

1.2

 

796

 

82.06

 

0.465

 

4.183

 

1.958

 

4.556

 

2.230

 

1.552

 

22

 

2009.03.24 11:55:43

 

12.0

 

33.317

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.728

 

6.0

 

189

 

1.420

 

1.159

 

6.607

 

1.911

 

5.896

 

2.382

 

1.425

 

23

 

2012.08.26 19:31:23

 

12.8

 

33.017

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.554

 

8.3

 

339

 

0.089

 

0.033

 

6.833

 

1.299

 

6.090

 

1.949

 

1.466

 

24

 

2014.10.21 00:36:58

 

12.3

 

65.151

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 149.040

 

12.8

 

33

 

46.19

 

149.3

 

5.537

 

2.846

 

5.017

 

2.970

 

1.331

 

25

 

2016.12.14 16:41:05

 

12.3

 

38.822

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 122.841

 

1.5

 

209

 

162.18

 

169.2

 

3.849

 

1.628

 

3.818

 

2.292

 

1.612

 

Примечание: * MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса модуля коэффициента прогнозной нелинейности K pn , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaadaabdaqaaabaaaaaaaaapeGaam4sa8aadaWgaaWcbaWd biaadchacaWGUbaapaqabaaakiaawEa7caGLiWoapeGaaiilaaaa@4445@ ** MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ от момента ретропрогноза до момента сильного землетрясения.

 

Таблица 5. Прогнозируемость затухания потока энергии после некоторых сильных землетрясений Северной Америки в 1900 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzafaeaaaaaaaaa8qacaWFtacaaa@3983@ 2016 гг.

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFwecaaa@3967@ п. п.

 

Землетрясение

 

Статистика прогнозируемости

 

Время

 

K

 

Гипоцентр

 

Кол-во определений

 

Δ t , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabfs5ae9aadaWgaaWcbaWdbiaadsha a8aabeaak8qacaGGSaaaaa@3E49@ сут

 

lg K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaabYgacaqGNbWaaqWaaeaacaWGlbWd amaaBaaaleaapeGaamiCaiaad6gaa8aabeaaaOWdbiaawEa7caGLiW oaaaa@42ED@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE6@

 

α* MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHjacSbOGQaaaaa@3E07@

 

широта

 

долгота

 

глубина

 

средн.*

 

на экстремуме K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadUeapaWaiigGBaaaleacIb4dbiac Ib4GWbGaiigGd6gaa8aabKGyacaaaa@426A@

 

макс.

 

средн.

 

макс.

 

средн.

 

1

 

1906.04.18 13:12:27

 

16.4

 

38.056

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 122.403

 

10.0

 

7693

 

4966

 

6669

 

2.872

 

1.311

 

3.145

 

1.936

 

1.270

 

2

 

1918.04.21 22:32:29

 

14.9

 

33.647

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.433

 

10.0

 

11923

 

10766

 

28699

 

2.770

 

0.428

 

3.145

 

0.642

 

1.363

 

3

 

1922.03.10 11:21:04

 

14.6

 

34.243

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 119.097

 

10.0

 

2190

 

9402

 

15864

 

2.705

 

0.748

 

2.947

 

1.059

 

1.325

 

4

 

1927.11.04 13:51:03

 

15.2

 

34.813

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.774

 

10.0

 

1664

 

15323

 

29965

 

3.639

 

1.303

 

3.441

 

1.988

 

1.439

 

5

 

1933.03.11 01:54:10

 

14.4

 

33.631

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.000

 

6.0

 

7705

 

6916

 

20038

 

5.906

 

1.761

 

5.421

 

2.372

 

1.695

 

6

 

1937.03.25 16:49:03

 

13.8

 

33.400

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.250

 

6.0

 

3487

 

1446

 

282.5

 

4.836

 

0.923

 

4.481

 

1.606

 

1.698

 

7

 

1940.05.19 04:36:41

 

15.2

 

32.844

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.381

 

6.0

 

4733

 

1370

 

2496

 

5.642

 

1.248

 

5.183

 

1.727

 

1.666

 

8

 

1947.04.10 15:58:06

 

14.6

 

34.983

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.532

 

6.0

 

4116

 

10256

 

16930

 

7.360

 

1.344

 

6.659

 

1.837

 

1.787

 

9

 

1952.07.21 11:52:15

 

16.1

 

34.958

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.998

 

6.0

 

43733

 

21174

 

23495

 

7.986

 

1.265

 

7.330

 

2.010

 

1.785

 

10

 

1956.02.09 14:32:42

 

15.0

 

31.832

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.231

 

6.0

 

8455

 

4573

 

2649

 

6.015

 

1.332

 

5.477

 

1.937

 

1.751

 

11

 

1959.08.18 06:37:20

 

15.6

 

44.630

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 110.891

 

10.0

 

4517

 

6949

 

13044

 

2.581

 

0.840

 

3.100

 

1.405

 

1.276

 

12

 

1962.10.29 02:42:54

 

12.3

 

34.349

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.866

 

6.0

 

314

 

800.2

 

28.05

 

3.202

 

0.923

 

3.289

 

1.532

 

1.733

 

13

 

1966.06.28 04:26:16

 

13.0

 

35.791

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.294

 

6.0

 

978

 

368.5

 

119.5

 

5.079

 

1.842

 

4.964

 

2.228

 

1.690

 

14

 

1971.02.09 14:00:41

 

14.7

 

34.416

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.370

 

9.0

 

13474

 

879.2

 

885.4

 

7.228

 

1.765

 

6.682

 

2.374

 

1.638

 

15

 

1975.06.01 01:38:48

 

12.7

 

34.512

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.488

 

0.1

 

2457

 

4940

 

6274

 

7.050

 

1.529

 

6.511

 

2.087

 

1.740

 

16

 

1980.05.25 19:44:50

 

14.5

 

37.696

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.750

 

6.0

 

40165

 

9666

 

13133

 

7.794

 

1.402

 

7.177

 

1.831

 

1.650

 

17

 

1984.11.23 18:08:25

 

14.0

 

37.460

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.607

 

8.1

 

29405

 

5322

 

5263

 

7.148

 

1.400

 

6.454

 

2.059

 

1.585

 

18

 

1987.11.24 01:54:14

 

13.8

 

33.080

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.780

 

5.0

 

3616

 

8422

 

9502

 

8.101

 

0.854

 

7.428

 

1.080

 

1.668

 

19

 

1992.04.25 18:06:04

 

15.5

 

40.368

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 124.316

 

14.9

 

1481

 

6810

 

8294

 

8.086

 

2.555

 

7.312

 

2.735

 

1.607

 

20

 

1995.09.25 04:47:29

 

12.2

 

35.809

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.616

 

8.5

 

13900

 

3884

 

6664

 

7.726

 

0.661

 

6.877

 

0.817

 

1.621

 

21

 

1999.10.16 09:46:44

 

15.5

 

34.603

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.265

 

13.7

 

91698

 

4320

 

5866

 

7.512

 

2.429

 

7.016

 

2.889

 

1.691

 

22

 

2002.11.03 22:12:41

 

16.7

 

63.517

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 147.444

 

4.9

 

21003

 

3543

 

5164

 

7.487

 

1.876

 

6.869

 

2.283

 

1.684

 

23

 

2006.10.08 02:48:26

 

11.6

 

46.850

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 121.600

 

1.6

 

3078

 

2217

 

3600

 

5.944

 

1.717

 

5.496

 

2.149

 

1.723

 

24

 

2010.07.07 23:53:33

 

12.9

 

33.417

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.475

 

12.3

 

24176

 

1464

 

2154

 

8.077

 

2.164

 

7.330

 

2.552

 

1.636

 

25

 

2014.07.17 11:49:33

 

13.8

 

60.349

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 140.333

 

10.0

 

5141

 

838.7

 

813.2

 

7.688

 

2.265

 

6.926

 

2.803

 

1.571

 

Примечание: * MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ рассчитывается как средневзвешенное с использованием в качестве веса модуля коэффициента прогнозной нелинейности K pn . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaadaabdaqaaabaaaaaaaaapeGaam4sa8aadaWgaaWcbaWd biaadchacaWGUbaapaqabaaakiaawEa7caGLiWoapeGaaiOlaaaa@4447@

 

Таблица 6. Характеристики зависимостей, соответствующих экстремальным значениям прогнозной нелинейности Kpn для некоторых сильных землетрясений Северной Америки (см. табл. 4)

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFwecaaa@3967@

 

Момент ретропрогноза

 

Аппроксимационная зависимость

 

n a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CF9@

 

n e MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGLbaa paqabaaaaa@3CFD@

 

T a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadsfapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CDF@

 

E a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CD0@

 

α MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHbaa@3C65@

 

k

 

L reg MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGYbGa amyzaiaadEgaa8aabeaaaaa@3EBE@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE6@

 

L kpn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGRbGa amiCaiaad6gaa8aabeaaaaa@3EC9@

 

Δ t , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8WrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabfs5ae9aadaWgaaWcbaWdbiaadsha a8aabeaak8qacaGGSaaaaa@3E49@ сут

 

Параметры выборки

 

шир., град.

 

долг., град.

 

глуб., км

 

рад., км

 

1

 

1934.06.06 22:40

 

E= E a +3.89· 10 12 × T a t 2.16 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaGWaaOWdbiadSb4FRaWkcaaIZaGaaiOlai aaiIdacaaI5aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWba aSqabeaapeGaaGymaiaaikdaaaGccqGHxdaTpaWaaqWaaeaapeGaam iva8aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baa paGaay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaikdacaGGUa GaaGymaiaaiAdaaaaaaa@5B33@

 

16

 

9

 

1934.06.08 12:59

 

2.59 · 1015

 

1.317

 

2.55 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

1.28

 

3.27

 

3.53

 

2.030

 

35.644

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.185

 

0.0

 

150.0

 

2

 

1937.08.31 23:52

 

E= E a +2.94· 10 9 × T a t 2.53 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaikdacaGGUaGaaGyoai aaisdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGaey41aq7damaaemaabaWdbiaadsfapaWaaSbaaS qaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWdaiaawEa7caGL iWoadaahaaWcbeqaa8qacqGHsislcaaIYaGaaiOlaiaaiwdacaaIZa aaaaaa@5983@

 

10

 

4

 

1937.09.01 16:16

 

1.15 · 1015

 

1.283

 

5.64 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 3

 

1.33

 

3.14

 

3.34

 

0.582

 

33.861

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.108

 

0.0

 

150.0

 

3

 

1940.05.19 02:26

 

E= E a +1.33· 10 13 × T a t 0.37 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIXaGaaiOlaiaaio dacaaIZaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaiodaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlai aaiodacaaI3aaaaaaa@5C18@

 

125

 

22

 

1940.05.19 13:21

 

8.79 · 1014

 

1.732

 

7.05 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 10

 

1.50

 

3.87

 

3.48

 

0.718

 

33.861

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.024

 

0.0

 

150.0

 

4

 

1947.04.11 07:24

 

E= E a +1.05· 10 8 × T a t 3.88 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIXaGaaiOlaiaaic dacaaI1aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGioaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8aada WgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaiodacaGGUaGaaGioai aaiIdaaaaaaa@5B6A@

 

22

 

8

 

1947.04.11 09:17

 

6.31 · 107

 

1.205

 

8.37 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 2

 

1.86

 

4.43

 

4.58

 

0.347

 

34.961

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.554

 

6.0

 

3.0

 

5

 

1952.07.21 23:11

 

E= E a +1.34· 10 11 × T a t 1.03 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIXaGaaiOlaiaaio dacaaI0aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaigdaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIXaGaaiOlai aaicdacaaIZaaaaaaa@5C11@

 

18

 

49

 

1952.07.22 00:15

 

2.67 · 109

 

1.492

 

6.67 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

1.74

 

4.08

 

4.42

 

5.768

 

35.299

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.459

 

10.0

 

15.0

 

6

 

1956.03.16 19:43

 

E= 4.49· 10 13 ln T a t / 7.18· 10 10 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpdaWcgaqaaiaaisda caGGUaGaaGinaiaaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8 aadaahaaWcbeqaa8qacaaIXaGaaG4maaaak8aacaaMb8+dbiabgkHi TiaabYgacaqGUbWdamaaemaabaWdbiaadsfapaWaaSbaaSqaa8qaca WGHbaapaqabaGccaaMb8+dbiabgkHiTiaadshaa8aacaGLhWUaayjc SdaapeqaaiaaiEdacaGGUaGaaGymaiaaiIdacaaMe8Uaai4Taiaays W7caaIXaGaaGima8aadaahaaWcbeqaa8qacqGHsislcaaIXaGaaGim aaaaaaaaaa@6297@

 

10

 

13

 

1956.03.16 19:43

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@

 

2.000

 

7.18 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 10

 

1.28

 

3.27

 

2.75

 

0.208

 

34.064

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.033

 

0.0

 

60.0

 

7

 

1962.11.12 15:57

 

E= E a +4.90· 10 13 × T a t 3.00 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaI0aGaaiOlaiaaiM dacaaIWaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaiodaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIZaGaaiOlai aaicdacaaIWaaaaaaa@5C17@

 

19

 

21

 

1962.11.19 12:48

 

3.82 · 1010

 

1.250

 

1.15 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 3

 

1.32

 

3.33

 

3.38

 

22.29

 

34.284

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.883

 

5.0

 

7.5

 

8

 

1965.09.10 14:55

 

E= 1.51· 10 16 ln T a t / 1.27· 10 10 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpdaWcgaqaaiaaigda caGGUaGaaGynaiaaigdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8 aadaahaaWcbeqaa8qacaaIXaGaaGOnaaaak8aacaaMb8+dbiabgkHi TiaabYgacaqGUbWdamaaemaabaWdbiaadsfapaWaaSbaaSqaa8qaca WGHbaapaqabaGccaaMb8+dbiaducOHsislcaWG0baapaGaay5bSlaa wIa7aaWdbeaacaaIXaGaaiOlaiaaikdacaaI3aGaaGjbVlaacElaca aMe8UaaGymaiaaicdapaWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaa icdaaaaaaaaa@63A6@

 

9

 

8

 

1965.09.25 16:48

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@

 

2.000

 

1.27 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 10

 

1.04

 

3.71

 

3.18

 

15.14

 

34.752

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.629

 

0.0

 

150.0

 

9

 

1970.09.12 14:10

 

E= 6.89· 10 12 ln T a t / 4.46· 10 10 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpdaWcgaqaaiaaiAda caGGUaGaaGioaiaaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8 aadaahaaWcbeqaa8qacaaIXaGaaGOmaaaak8aacaaMb8+dbiabgkHi TiaabYgacaqGUbWdamaaemaabaWdbiaadsfapaWaaSbaaSqaa8qaca WGHbaapaqabaGccaaMb8+dbiaducOHsislcaWG0baapaGaay5bSlaa wIa7aaWdbeaacaaI0aGaaiOlaiaaisdacaaI2aGaaGjbVlaacElaca aMe8UaaGymaiaaicdapaWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaa icdaaaaaaaaa@63B6@

 

13

 

8

 

1970.09.12 14:10

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@

 

2.000

 

4.46 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 10

 

1.43

 

3.56

 

3.04

 

0.451

 

34.422

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.676

 

0.0

 

60.0

 

10

 

1975.06.01 01:35

 

E= E a +1.10· 10 9 × T a t 0.26 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIXaGaaiOlaiaaig dacaaIWaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGyoaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8aada WgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaGOmai aaiAdaaaaaaa@5B5C@

 

19

 

2

 

1975.06.01 01:36

 

1.52 · 1014

 

1.795

 

2.40 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.59

 

4.68

 

4.26

 

0.002

 

34.422

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.368

 

0.0

 

60.0

 

11

 

1978.01.26 12:57

 

E= E a +1.39· 10 12 × T a t 1.16 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaigdacaGGUaGaaG4mai aaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGOmaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6cacaaIXa GaaGOnaaaaaaa@5A33@

 

77

 

4

 

1978.03.12 14:47

 

5.75 · 1010

 

1.463

 

4.85 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

1.23

 

3.47

 

3.84

 

49.71

 

32.576

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.282

 

10.0

 

7.5

 

12

 

1980.05.25 18:13

 

E= E a +6.45· 10 9 × T a t 1.14 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaiAdacaGGUaGaaGinai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGaey41aq7damaaemaabaWdbiaadsfapaWaaSbaaS qaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWdaiaawEa7caGL iWoadaahaaWcbeqaa8qacqGHsislcaaIXaGaaiOlaiaaigdacaaI0a aaaaaa@597F@

 

14

 

6

 

1980.05.25 18:35

 

1.19 · 1012

 

1.466

 

5.37 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 5

 

1.95

 

5.30

 

5.95

 

0.070

 

37.654

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.723

 

5.0

 

7.5

 

13

 

1982.06.10 23:10

 

E= E a +8.43· 10 13 × T a t 1.56 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaI4aGaaiOlaiaais dacaaIZaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaiodaaaGccWGyaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIXaGaaiOlai aaiwdacaaI2aaaaaaa@5C18@

 

91

 

407

 

1982.09.01 15:47

 

1.36 · 1011

 

1.391

 

7.85 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

1.34

 

3.39

 

3.76

 

173.9

 

35.734

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.735

 

4.0

 

3.0

 

14

 

1984.11.23 18:57

 

E= E a +3.42· 10 7 × T a t 1.04 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaiodacaGGUaGaaGinai aaikdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI3aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6cacaaIWaGaaG inaaaaaaa@5A6A@

 

13

 

25

 

1984.11.23 19:00

 

2.19 · 107

 

1.491

 

4.02 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

2.01

 

5.87

 

6.60

 

0.036

 

37.424

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.620

 

10.0

 

3.0

 

15

 

1987.11.24 12:44

 

E= E a +6.53· 10 8 × T a t 1.04 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadIbOHRaWkcaaI2aGaaiOlaiaaiw dacaaIZaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGioaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8aada WgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaigdacaGGUaGaaGimai aaisdaaaaaaa@5B5A@

 

31

 

15

 

1987.11.24 13:42

 

1.08 · 108

 

1.490

 

9.57 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 5

 

2.11

 

7.16

 

8.07

 

0.144

 

33.002

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.837

 

0.0

 

3.0

 

16

 

1989.03.06 05:01

 

E= E a +2.36· 10 14 × T a t 1.21 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaikdacaGGUaGaaG4mai aaiAdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGinaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaigdacaGGUaGaaG Omaiaaigdaaaaaaa@5B23@

 

141

 

623

 

1989.05.25 02:24

 

2.32 · 1011

 

1.453

 

6.25 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.20

 

3.67

 

4.10

 

411.4

 

34.149

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.684

 

10.0

 

7.5

 

17

 

1992.06.28 10:57

 

E= E a +9.65· 10 8 × T a t 0.72 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaI5aGaaiOlaiaaiA dacaaI1aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGioaaaakiabgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiadSbOHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG4nai aaikdaaaaaaa@5B6E@

 

21

 

4

 

1992.06.28 11:56

 

2.07 · 1010

 

1.582

 

1.23 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 5

 

1.97

 

8.63

 

8.34

 

0.042

 

34.206

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.451

 

2.0

 

3.0

 

18

 

1995.09.13 18:09

 

E= E a +1.78· 10 10 × T a t 1.25 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaigdacaGGUaGaaG4nai aaiIdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa aKqzqdWdbiaaigdacaaIWaaaaOGamWgGgEna0+aadaabdaqaa8qaca WGubWdamaaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadsha a8aacaGLhWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6 cacaaIYaGaaGynaaaaaaa@5C66@

 

126

 

33

 

1995.09.20 23:36

 

3.55 · 108

 

1.445

 

5.54 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 5

 

1.70

 

6.91

 

7.79

 

7.221

 

35.756

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.631

 

4.0

 

1.5

 

19

 

1999.10.20 16:23

 

E= E a +1.42· 10 10 × T a t 1.45 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaigdacaGGUaGaaGinai aaikdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGimaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6cacaaI0a GaaGynaaaaaaa@5A2D@

 

25

 

101

 

1999.10.21 02:02

 

2.06 · 109

 

1.408

 

1.52 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

2.11

 

5.56

 

6.04

 

2.741

 

34.853

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.395

 

2.0

 

3.0

 

20

 

2002.10.24 01:52

 

E= E a +2.68· 10 14 × T a t 1.09 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaikdacaGGUaGaaGOnai aaiIdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGinaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6cacaaIWa GaaGyoaaaaaaa@5A3A@

 

48

 

188

 

2002.10.24 09:41

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.19 · 109

 

1.478

 

2.54 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

2.21

 

4.89

 

5.35

 

11.76

 

63.593

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 147.604

 

0.0

 

30.0

 

21

 

2005.09.01 14:17

 

E= E a +1.76· 10 9 × T a t 0.41 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIXaGaaiOlaiaaiE dacaaI2aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGyoaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8aada WgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaGinai aaigdaaaaaaa@5B65@

 

28

 

2

 

2005.09.01 14:52

 

1.86 · 1011

 

1.712

 

7.04 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.37

 

4.56

 

4.18

 

0.465

 

33.146

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.644

 

0.0

 

3.0

 

22

 

2009.03.23 08:06

 

E= E a +2.25· 10 8 × T a t 1.42 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgUcaRiaaikdacaGGUaGaaGOmai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI4aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGymaiaac6cacaaI0aGaaG Omaaaaaaa@5A6D@

 

18

 

5

 

2009.03.23 17:05

 

1.86 · 108

 

1.414

 

7.31 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

1.87

 

5.90

 

6.61

 

1.172

 

33.320

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.721

 

6.0

 

1.5

 

23

 

2012.08.26 18:43

 

E= E a +9.37· 10 7 × T a t 1.16 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaI5aGaaiOlaiaaio dacaaI3aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaG4naaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8aada WgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGaay5b SlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaigdacaGGUaGaaGymai aaiAdaaaaaaa@5B6B@

 

39

 

33

 

2012.08.26 19:24

 

9.43 · 1011

 

1.464

 

4.05 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

2.05

 

6.09

 

6.83

 

0.088

 

33.002

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.558

 

6.0

 

3.0

 

24

 

2014.05.24 17:06

 

E= E a +3.12· 10 23 × T a t 5.93 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiadSbOHRaWkcaaIZaGaaiOlaiaaig dacaaIYaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGOmaiaaiodaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaI1aGaaiOlai aaiMdacaaIZaaaaaaa@5C1F@

 

80

 

1475

 

2015.01.10 03:58

 

1.17 · 1011

 

1.144

 

2.20 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 3

 

1.15

 

5.02

 

5.54

 

158.3

 

65.120

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 149.002

 

0.0

 

15.0

 

25

 

2016.06.28 12:47

 

E= E a +2.45· 10 13 × T a t 1.12 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiad2bOHRaWkcaaIYaGaaiOlaiaais dacaaI1aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaiodaaaGccWGDaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIXaGaaiOlai aaigdacaaIYaaaaaaa@5C2A@

 

1961

 

302

 

2017.01.11 01:37

 

1.48 · 1010

 

1.472

 

9.63 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.54

 

3.49

 

3.85

 

182.5

 

38.821

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 122.854

 

2.0

 

1.5

 

Примечание: n a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3F7A@ и n e MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGLbaa paqabaaaaa@3F7E@ MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ число событий в аппроксимационной и экстраполяционной (прогнозной) частях последовательности, значения асимптоты X a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadIfapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3F64@ и коэффициента k приведены с учетом размерности параметра E MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ Дж; L reg =lg K reg , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGYbGa amyzaiaadEgaa8aabeaak8qacqGH9aqpcaqGSbGaae4zamaaemaaba Gaam4sa8aadaWgaaWcbaWdbiaadkhacaWGLbGaam4zaaWdaeqaaaGc peGaay5bSlaawIa7aiaacYcaaaa@4C1B@ L kpn =lg K pn . MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGRbGa amiCaiaad6gaa8aabeaak8qacqGH9aqpcaqGSbGaae4zamaaemaaba Gaam4sa8aadaWgaaWcbaWdbiaadchacaWGUbaapaqabaaak8qacaGL hWUaayjcSdGaaiOlaaaa@4B43@

 

Таблица 7. Характеристики зависимостей затухания потока сейсмической энергии после некоторых сильных землетрясений Северной Америки (см. табл. 5), соответствующие экстремумам прогнозной нелинейности K pn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadUeapaWaiGfGBaaaleacyb4dbiac yb4GWbGaiGfGd6gaa8aabKawacaaaa@4237@

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFwecaaa@3967@

 

Момент ретропрогноза

 

Аппроксимационная зависимость

 

n a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CF8@

 

n e MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaad6gapaWaaSbaaSqaa8qacaWGLbaa paqabaaaaa@3CFC@

 

T a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadsfapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CDE@

 

E a MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweapaWaaSbaaSqaa8qacaWGHbaa paqabaaaaa@3CCF@

 

α MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabeg7aHbaa@3C64@

 

k

 

L reg MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGYbGa amyzaiaadEgaa8aabeaaaaa@3EBD@

 

L p MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGWbaa paqabaaaaa@3CE5@

 

L kpn MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadYeapaWaaSbaaSqaa8qacaWGRbGa amiCaiaad6gaa8aabeaaaaa@3EC8@

 

Δ t , MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacH8GrFr0lbbf9q8WrFfeuY= Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiabfs5ae9aadaWgaaWcbaWdbiaadsha a8aabeaak8qacaGGSaaaaa@3E48@ сут

 

Параметры выборки

 

шир., град.

 

долг., град.

 

глуб., км

 

рад., км

 

1

 

1996.01.23 10:20

 

E= E a 6.03· 10 17 × T a t 1.30 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiAdacaGGUaGaaGimai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaG4naaaakiadSbOHxdaTdaabdaqaaiaadsfapaWaaS baaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaGaay5bSlaa wIa7amaaCaaaleqabaGaeyOeI0IaaGymaiaac6cacaaIZaGaaGimaa aaaaa@5AF1@

 

5850

 

5557

 

1905.03.19 09:45

 

2.51 · 1016

 

1.435

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 3.73 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

2.50

 

3.14

 

2.87

 

6669

 

38.367

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 122.675

 

40.0

 

60.0

 

2

 

1938.05.31 08:34

 

E= E a 2.23· 10 15 × T a t 0.70 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaikdacaGGUaGaaGOmai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGynaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI3a GaaGimaaaaaaa@5A3A@

 

123

 

2737

 

1917.11.27 03:53

 

8.00 · 1014

 

1.589

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.90 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 9

 

1.68

 

2.88

 

2.77

 

28699

 

33.772

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.514

 

20.0

 

30.0

 

3

 

1950.01.24 21:57

 

E= E a 1.07· 10 15 × T a t 1.11 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGimai aaiEdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGynaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaigdacaGGUaGaaG ymaiaaigdaaaaaaa@5B2B@

 

66

 

1111

 

1921.12.11 15:31

 

3.98 · 1014

 

1.475

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.48 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.96

 

2.95

 

2.71

 

15864

 

34.311

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.839

 

0.0

 

30.0

 

4

 

1934.12.17 11:09

 

E= E a 6.90· 10 14 × T a t 0.91 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiad2bOHsislcaaI2aGaaiOlaiaaiM dacaaIWaGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaisdaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlai aaiMdacaaIXaaaaaaa@5C36@

 

18

 

1052

 

1927.10.11 13:46

 

2.59 · 1015

 

1.523

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 3.52 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

1.58

 

3.44

 

3.64

 

29965

 

34.422

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.726

 

0.0

 

60.0

 

5

 

1933.06.23 14:54

 

E= E a 4.27· 10 11 × T a t 0.54 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaisdacaGGUaGaaGOmai aaiEdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGymaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG ynaiaaisdaaaaaaa@5B32@

 

20

 

77

 

1933.03.11 01:53

 

2.58 · 1014

 

1.650

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 6.35 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

2.42

 

5.42

 

5.91

 

20039

 

33.610

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.022

 

5.0

 

7.5

 

6

 

1937.03.27 12:27

 

E= E a 4.43· 10 11 × T a t 0.22 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaisdacaGGUaGaaGinai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGymaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG Omaiaaikdaaaaaaa@5B2B@

 

24

 

52

 

1937.03.25 16:49

 

6.77 · 1013

 

1.819

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.23 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 9

 

1.41

 

4.47

 

4.84

 

282.5

 

33.347

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.268

 

0.0

 

60.0

 

7

 

1940.06.01 23:59

 

E= E a 1.89· 10 12 × T a t 0.47 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGioai aaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGOmaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI0a GaaG4naaaaaaa@5A46@

 

29

 

33

 

1940.05.19 04:36

 

1.88 · 1015

 

1.682

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.04 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

2.00

 

5.18

 

5.64

 

2496

 

32.629

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.089

 

0.0

 

60.0

 

8

 

1947.04.11 18:43

 

E= E a 1.15· 10 12 × T a t 0.30 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGymai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGOmaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaIZa GaaGimaaaaaaa@5A33@

 

46

 

115

 

1947.04.10 15:58

 

4.02 · 1014

 

1.772

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.65 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 9

 

1.55

 

6.66

 

7.36

 

16930

 

34.958

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.583

 

5.0

 

7.5

 

9

 

1952.07.23 22:32

 

E= E a 1.40· 10 13 × T a t 0.23 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGinai aaicdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaG4maaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG Omaiaaiodaaaaaaa@5B28@

 

42

 

1026

 

1952.07.21 11:52

 

1.26 · 1016

 

1.812

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 8.57 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 11

 

1.69

 

7.33

 

7.99

 

23495

 

35.030

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.884

 

0.0

 

15.0

 

10

 

1956.02.11 06:11

 

E= E a 2.43· 10 13 × T a t 0.19 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaikdacaGGUaGaaGinai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaG4maaaakiad2bOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG ymaiaaiMdaaaaaaa@5B3B@

 

32

 

89

 

1956.02.09 14:32

 

1.23 · 1015

 

1.842

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 2.62 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 11

 

1.40

 

5.48

 

6.02

 

2649

 

31.796

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.122

 

0.0

 

30.0

 

11

 

1981.04.15 18:46

 

E= E a 5.85· 10 13 × T a t 0.17 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiaacobicaaI1aGaaiOlaiaaiIdaca aI1aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqabeaa peGaaGymaiaaiodaaaGccWaBaA41aq7damaaemaabaWdbiaadsfapa WaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWdaiaa wEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlaiaaig dacaaI3aaaaaaa@5B02@

 

89

 

4317

 

1959.08.18 06:37

 

4.07 · 1015

 

1.858

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 8.34 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 12

 

1.42

 

3.10

 

2.58

 

13044

 

44.462

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 111.429

 

0.0

 

60.0

 

12

 

1962.11.02 22:35

 

E= E a 1.59· 10 10 × T a t 0.38 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGynai aaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGimaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacWaBaAOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlai aaiodacaaI4aaaaaaa@5C29@

 

15

 

8

 

1962.10.29 02:42

 

9.52 · 1012

 

1.723

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.15 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

1.59

 

3.29

 

3.20

 

28.05

 

34.222

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.867

 

10.0

 

15.0

 

13

 

1966.07.09 01:12

 

E= E a 9.29· 10 8 × T a t 0.61 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiMdacaGGUaGaaGOmai aaiMdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI4aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI2aGaaG ymaaaaaaa@5A83@

 

52

 

15

 

1966.06.28 04:26

 

1.07 · 1013

 

1.623

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 5.71 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

2.62

 

4.96

 

5.08

 

119.5

 

35.856

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 120.305

 

5.0

 

7.5

 

14

 

1971.02.11 17:35

 

E= E a 1.27· 10 10 × T a t 0.52 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGOmai aaiEdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGimaaaakiad2bOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG ynaiaaikdaaaaaaa@5B36@

 

27

 

38

 

1971.02.09 14:00

 

5.02 · 1014

 

1.659

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 5.11 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

2.64

 

6.68

 

7.23

 

885.4

 

34.404

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.392

 

8.0

 

3.0

 

15

 

1975.06.06 13:06

 

E= E a 3.43· 10 9 × T a t 0.25 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiodacaGGUaGaaGinai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaIYaGaaG ynaaaaaaa@5A7A@

 

39

 

25

 

1975.06.01 01:38

 

5.02 · 1012

 

1.798

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 9.28 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

1.77

 

6.51

 

7.05

 

6274

 

34.515

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.502

 

0.0

 

1.5

 

16

 

1980.06.03 07:24

 

E= E a 2.16· 10 10 × T a t 0.43 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiad2bOHsislcaaIYaGaaiOlaiaaig dacaaI2aGaaGjbVlaacElacaaMe8UaaGymaiaaicdapaWaaWbaaSqa beaapeGaaGymaiaaicdaaaGccWaBaA41aq7damaaemaabaWdbiaads fapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWd aiaawEa7caGLiWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlai aaisdacaaIZaaaaaaa@5C29@

 

61

 

268

 

1980.05.25 19:44

 

3.17 · 1014

 

1.698

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.56 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

2.58

 

7.18

 

7.79

 

13133

 

37.743

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.760

 

5.0

 

7.5

 

17

 

1984.11.30 08:02

 

E= E a 1.76· 10 9 × T a t 0.90 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaG4nai aaiAdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGaey41aq7damaaemaabaWdbiaadsfapaWaaSbaaS qaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWdaiaawEa7caGL iWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlaiaaiMdacaaIWa aaaaaa@598C@

 

59

 

173

 

1984.11.23 18:07

 

1.32 · 1014

 

1.525

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 2.81 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 5

 

2.88

 

6.45

 

7.15

 

5263

 

37.454

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 118.597

 

9.0

 

1.5

 

18

 

1987.11.26 11:58

 

E= E a 4.31· 10 9 × T a t 0.43 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaisdacaGGUaGaaG4mai aaigdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI0aGaaG 4maaaaaaa@5A78@

 

35

 

39

 

1987.11.24 01:54

 

6.35 · 1013

 

1.700

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 4.65 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

2.40

 

7.43

 

8.10

 

9502

 

33.074

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 115.783

 

4.0

 

3.0

 

19

 

1992.04.26 09:49

 

E= E a 5.65· 10 10 × T a t 0.57 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiwdacaGGUaGaaGOnai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGimaaaakiabgEna0+aadaabdaqaa8qacaWGubWdam aaBaaaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGL hWUaayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI1a GaaG4naaaaaaa@5A43@

 

104

 

673

 

1992.04.25 18:06

 

3.16 · 1015

 

1.639

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 3.07 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

2.49

 

7.31

 

8.09

 

8294

 

40.394

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 124.316

 

10.0

 

7.5

 

20

 

1995.09.25 07:00

 

E= E a 6.05· 10 8 × T a t 0.55 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiAdacaGGUaGaaGimai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI4aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI1aGaaG ynaaaaaaa@5A7D@

 

16

 

78

 

1995.09.25 04:47

 

1.61 · 1012

 

1.646

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 4.86 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

1.58

 

6.88

 

7.73

 

6664

 

35.809

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 117.622

 

8.0

 

1.5

 

21

 

1999.11.12 13:18

 

E= E a 9.95· 10 9 × T a t 0.74 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiMdacaGGUaGaaGyoai aaiwdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGaey41aq7damaaemaabaWdbiaadsfapaWaaSbaaS qaa8qacaWGHbaapaqabaGcpeGaeyOeI0IaamiDaaWdaiaawEa7caGL iWoadaahaaWcbeqaa8qacqGHsislcaaIWaGaaiOlaiaaiEdacaaI0a aaaaaa@5997@

 

106

 

588

 

1999.10.16 09:46

 

3.19 · 1015

 

1.574

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 3.76 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

3.50

 

6.96

 

7.51

 

5866

 

34.643

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.278

 

15.0

 

7.5

 

22

 

2002.11.09 00:36

 

E= E a 1.28· 10 11 × T a t 0.54 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaigdacaGGUaGaaGOmai aaiIdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaIXaGaaGymaaaakiadSbOHxdaTpaWaaqWaaeaapeGaamiva8 aadaWgaaWcbaWdbiaadggaa8aabeaak8qacqGHsislcaWG0baapaGa ay5bSlaawIa7amaaCaaaleqabaWdbiabgkHiTiaaicdacaGGUaGaaG ynaiaaisdaaaaaaa@5B30@

 

39

 

240

 

2002.11.03 22:12

 

5.01 · 1016

 

1.651

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 1.36 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 7

 

3.11

 

6.87

 

7.49

 

5164

 

63.490

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 147.373

 

0.0

 

7.5

 

23

 

2006.10.15 04:10

 

E= E a 2.33· 10 9 × T a t 0.16 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaikdacaGGUaGaaG4mai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI5aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaIXaGaaG Onaaaaaaa@5A78@

 

54

 

68

 

2006.10.08 02:48

 

4.02 · 1011

 

1.860

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 4.89 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 8

 

1.45

 

5.50

 

5.94

 

3600

 

46.842

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 121.602

 

4.0

 

3.0

 

24

 

2010.07.08 03:14

 

E= E a 6.80· 10 7 × T a t 0.44 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiAdacaGGUaGaaGioai aaicdacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI3aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI0aGaaG inaaaaaaa@5A7D@

 

31

 

131

 

2010.07.07 23:53

 

7.98 · 1012

 

1.696

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 9.09 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 6

 

2.37

 

7.33

 

8.08

 

2154

 

33.433

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 116.466

 

14.0

 

3.0

 

25

 

2014.07.17 19:00

 

E= E a 5.33· 10 6 × T a t 0.99 MathType@MTEF@5@5@+= feaahqart1ev3aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaeXafv3ySLgzGmvETj2BSbqefm0B 1jxALjhiov2DaebbnrfifHhDYfgasaacPqFz0xf9v8qqaqFD0xXdHa Vhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0=yr0RYxir=Jbba9q8aq 0=yq=He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaWaaeqabaabae aafaaakeaaqaaaaaaaaaWdbiaadweacqGH9aqpcaWGfbWdamaaBaaa leaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaaiwdacaGGUaGaaG4mai aaiodacaaMe8Uaai4TaiaaysW7caaIXaGaaGima8aadaahaaWcbeqa a8qacaaI2aaaaOGamWgGgEna0+aadaabdaqaa8qacaWGubWdamaaBa aaleaapeGaamyyaaWdaeqaaOWdbiabgkHiTiaadshaa8aacaGLhWUa ayjcSdWaaWbaaSqabeaapeGaeyOeI0IaaGimaiaac6cacaaI5aGaaG yoaaaaaaa@5A83@

 

27

 

31

 

2014.07.17 11:49

 

6.31 · 1013

 

1.502

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 8.40 · 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqz+caeaaaaaaaaa8qacaWFtacaaa@3A00@ 4

 

2.68

 

6.89

 

7.69

 

813.2

 

60.359

 

MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGeaeaaaaaaaaa8qacaWFtacaaa@3963@ 140.287

 

10.0

 

3.0

 

Примечание: см. табл. 6.

 

Рис. 4. Пространственное распределение сейсмичности и прогнозируемость сильных землетрясений Северной Америки в 1900–2016 гг. Точками серого цвета показано положение гипоцентров землетрясений по данным каталога Геологической службы США. Круги соответствуют гипоцентрам сильных землетрясений; интенсивность заливки верхнего и нижнего полукружий пропорциональна, соответственно, форшоковой и афтершоковой прогнозируемости данного землетрясения (по экстремуму прогнозной нелинейности).

 

Высокая прогнозируемость сейсмического потока (сохранение аппроксимационных тенденций при их экстраполяции в будущее, см. табл. 1) свидетельствует, что уравнение (2) при использовании описанной методики адекватно моделирует динамику потока сейсмической энергии. Это делает возможным применение уравнения (2) для дифференцирования потоковых характеристик сейсмичности, т. е. для определения скоростей и ускорений сейсмического потока. В свою очередь анализ пространственного распределения этих производных позволяет определить локализацию имеющихся тенденций к изменению сейсмичности. Поскольку сильные землетрясения приурочены к экстремумам прогнозируемой нелинейности сейсмического потока (см. рис. 1), то пространственные локализации с экстремальными тенденциями к его изменчивости представляют интерес для прогноза как самих сильных землетрясений, так и афтершокового затухания сейсмичности, т. е. именно в этих локализациях имеют смысл экстраполяции существующих тенденций в будущее. По сути мы получаем комбинацию методов саморазвивающихся процессов и картирования сейсмической активности по плотности сейсмического потока [Тихонов, 2006; 2009].

Потенциальную эффективность изложенной методики отчасти подтверждают ранее полученные данные [Малышев, 2014]: на картах ускорений сейсмической активности, построенных при сканировании с шагом 10 км (гипоцентральный радиус выборок 15 км) зона предстоящего Восточно-Японского землетрясения (11.03.2011 г., M = 9.0) начинает отчетливо выделяться за несколько дней до толчка. Зона подготовки имеет размеры примерно 100×80×40 км, что существенно превышает шаг сканирования. Это также согласуется с результатами данной работы (см. табл. 2), свидетельствующими о том, что прогнозируемость сильных землетрясений проявляется на средних (от 7.5 до 30 км) и больших (60 и 150 км) радиусах гипоцентральных выборок. Таким образом, предлагаемая методика устанавливает, как минимум, наличие перед Восточно-Японским землетрясением хорошо выраженных предвестников, использование которых позволило бы расширить интервал времени на предотвращение разрушительных последствий землетрясения с 10 MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ 30 минут (время достижения волной цунами побережья) до нескольких суток.

Положительный ответ на вопросы первой группы (из сформулированных во введении) позволяет в общих чертах наметить перспективы практического использования прогнозируемости сейсмического потока. Если количественно определить активизацию сейсмического потока как величину, обратно пропорциональную расчетному времени для удвоения скорости выделения энергии, то при помощи этой величины возможно картирование зон быстрой активизации (рис. 5). Использование гипоцентров землетрясений в выборках с наибольшей величиной активизации позволяет статистически установить зону ее максимума и, далее, прогнозировать развитие сейсмичности уже в пределах этой зоны, т. е. выявлять имеющиеся тенденции выделения энергии и на их основе оценивать вероятность сильных землетрясений.

Естественно, что рис. 5 лишь иллюстрирует принципиальные возможности 3D-картирования перед сильными землетрясениями. Окончательный вариант подобного картирования будет определен на третьем (из упомянутых во Введении) этапе исследований. Однако для перехода к этому этапу необходимо рассмотреть статистические данные по устойчивости экстраполяций потока энергии в зависимости от параметров уравнения ДСПП и условий формирования выборок.

 

Рис. 5. Зоны форшоковой активизации перед некоторыми сильными землетрясениями: 01 – за сутки до землетрясения 08.06.1934 г. (M = 5.8) 17 – за 30 суток до землетрясения 28.06.1992 г. (M= 7.3) 20 – за 5 суток до землетрясения 03.11.2002 г. (M = 7.9) Нумерация соответствует табл. 4 и верхней части рис. 1. Двойной круг с перекрестием – гипоцентр будущего сильного землетрясения; окружности соответствуют выборкам, в которых выявлена активизация; крестики – гипоцентры землетрясений, входящих в последовательности активизации; прямоугольник ограничивает средневзвешенную зону активизации ±3σ от ее статистического центра).

 

Тем не менее полученные результаты позволяют утверждать, что мониторинг на основе метода саморазвивающихся процессов с предварительным картированием нелинейности сейсмического потока для Северной Америки имеет смысл на всех радиусах гипоцентральных выборок: с повышением радиуса выборок увеличивается число сильных землетрясений, имеющих прогнозируемость по потоку сейсмической энергии, тогда как уменьшение радиуса приводит к возрастанию уровней прогнозируемости и прогнозной нелинейности потока энергии, а также к повышению точности определения пространственного положения экстремумов нелинейности потока сейсмической энергии, к которым приурочены сильные землетрясения.

ВЫВОДЫ

Проанализированный для Северной Америки поток сейсмической энергии показывает хорошую прогнозируемость. Следовательно, уравнение (2) при использовании описанной методики адекватно моделирует динамику сейсмичности и его можно использовать для картирования экстремальной нелинейности сейсмического потока. Комбинация метода саморазвивающихся процессов с предварительным картированием позволяет перейти к прогнозу сейсмичности в зонах экстремальной нелинейности. Полученные результаты демонстрируют очень хорошие перспективы аппроксимационно-экстраполяционного подхода для прогноза как самих сильных землетрясений, так и последующего афтершокового затухания сейсмической активности. При этом суммарная энергия землетрясений E представляет собой характеристику сейсмического потока, которую возможно непосредственно использовать для прогноза энергии землетрясений. Получение аналогичных результатов по нескольким регионам на основе различных источников сейсмических данных позволяет перейти ко второму этапу исследований MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFtacaaa@39A3@ обобщающей оценке прогностического потенциала уравнения ДСПП и статистической настройке его параметров на максимальную эффективность прогноза трендов потока сейсмической энергии.

Фининсирование работы

Исследование выполнено в рамках государственного задания ИГГ УрО РАН MathType@MTEF@5@5@+= feaahqart1ev3aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaqefeKCPfgBaG qbaKqzGfaeaaaaaaaaa8qacaWFwecaaa@39A7@ АААА-А19-119072990020-6.

 


[1] https://earthquake.usgs.gov/earthquakes/search/

[2] Здесь и далее прогнозная нелинейность определяется величиной прогнозируемость величиной

About the authors

A. I. Malyshev

Zavaritsky Institute of Geology and Geochemistry, Ural Branch, Russian Academy of Sciences

Author for correspondence.
Email: malyshev@igg.uran.ru

Russian Federation, Yekaterinburg

References

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Supplementary files

Supplementary Files Action
1.
Fig. 1. Predictability of the flow of seismic energy and strong earthquakes in North America in 1962–2016. The circles correspond to the extremes of the predicted nonlinearity of strong earthquakes. The upper half of the diagram characterizes forecasts for the activation of seismic flow and foreshock predictability of strong earthquakes, the lower half characterizes forecasts for a decrease in seismic activity and aftershock predictability. The numbering of strong earthquakes in the upper part of the diagram corresponds to the table. 4, tab. 6 and fig. 3; at the bottom of the diagram - table. 5 and tab. 7.

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2.
Fig. 2. The predicted significance of the degree of non-linearity index α. See note to fig. one.

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3.
Fig. 3. Graphs of retro-predictive definitions corresponding to the nonlinear predictability maxima of some strong earthquakes: 1 - actual data curve, 2 - calculated curve, 3 - error band (± 3σ) 4 - retro-forecast moment, 5 - strong earthquake. The sequence numbers of the graphs correspond to the numbering in the table. 4 and tab. 6. The graphs on the left characterize the approximation parts of the forecast definitions, on the right - the forecast dependencies in general. The intersection of the dotted vertical and horizontal lines on the graphs corresponds to the “current” values ​​of time and parameter, to the left and below this intersection is the “past”, to the right and higher is the “future”. Dashed lines show the position of the asymptotes Ta and Xa

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4.
Fig. 4. The spatial distribution of seismicity and the predictability of strong earthquakes in North America in 1900–2016. Gray dots indicate the location of the earthquake hypocenters according to the catalog of the US Geological Survey. The circles correspond to the hypocenters of strong earthquakes; the fill intensity of the upper and lower semicircles is proportional, respectively, to the foreshock and aftershock predictability of this earthquake (according to the extremum of the predicted nonlinearity).

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5.
Fig. 5. Zones of foreshock activation before some major earthquakes: 01 - one day before the earthquake 06/06/1934 (M = 5.8) 17 - 30 days before the earthquake 06/28/1992 (M = 7.3) 20 - 5 days before the earthquake November 3, 2002 (M = 7.9) The numbering corresponds to the table. 4 and the upper part of Fig. 1. A double circle with a crosshair - a hypocenter of the future strong earthquake; circles correspond to samples in which activation is detected; crosses - hypocenters of earthquakes included in the activation sequence; the rectangle limits the weighted average activation zone ± 3σ from its statistical center).

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