Product characteristics forecasting model with support vectore machines


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Abstract

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

About the authors

I Kovalev

Siberian State Airspace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk

Siberian State Airspace University named after academician M. F. Reshetnev, Russia, Krasnoyarsk

N S Y urkov

Siberian Federal University, Russia, Krasnoyarsk

Siberian Federal University, Russia, Krasnoyarsk

References

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  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.
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  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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Copyright (c) 2009 Kovalev I., Y urkov N.S.

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