Product characteristics forecasting model with support vectore machines


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Аннотация

Numerical models with support vector machines are used for forecasting material's properties depending on their production parameters. The paper includes practical forecasting results.

Об авторах

I Kovalev

N S Y urkov

Список литературы

  1. Yurkov, N. S. Application of support vector machines to multiple nonlinear regression problem (at the example of mechanical properties of aluminium alloys) / N. S. Yurkov // Control systems and information technologies. 2009. No 1.2 (35). P . 307-312.
  2. Gulyayev,A. P. Metallography /A. P. Gulyayev. 6th ed. M. : Metallurgiya, 1986. 544 p. (in Russian)
  3. DIN EN 515-1993.Aluminium and aluminium alloys; wrought products; temper designations; DIN-Mittei-lungen von 1996. Nr. 12. S. A 971 (Tabelle 4 , S. 11 2. Spalte gendert).
  4. Data analysis methods and models: OLAP and Data Mining/A.A.Barsegyan, M. S.Kupriyanov,V .V . Stepanenko, I. I. Kholod. SPb. : BHV-Peterburg, 2004. 336 p.
  5. Kecman, V. Support Vector Machine Basics. School of engineering report 616 / Vojislav Kecman. Auckland : The University ofAuckland, 2004. 54 p.
  6. Vapnik, V. N. Estimation of dependences based on empirical data / V. N. Vapnik. M. : Nauka, 1979. 499 p. (in Russian)
  7. Witten, Ian H. Data Mining: PracticalMachine Learning Tools and Techniques / Ian H. Witten, Eibe Frank. 2nd ed. San Francisco : Morgan Kaufmann Publishers, 2005. 525 p.

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© Kovalev I., Y urkov N.S., 2009

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