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《Journal of Southern Yangtze University》 2006-04
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Model and Application Based on Supportable Recursive Vector for Forecasting Steel Mechanics Performance

LIN Yubai,LUO Jian~*(Department of Automation,Xiamen University,Xiamen 361005,China)  
The quality of final steel product will be raised efficiently by accurately forecasting the mechanics performances based on the chemical components and adjusting related control strategy.SVM is a kind of mechine learning way based on statistics theory.A εSVM method based on this arithmetic and its deduce are introduced.Then,a model of steel mechanics performances based on εSVM is constructed.Finally,an application of this model through practical data indicates that εSVM get a higher precision than Excel recursive forecast.
【CateGory Index】: TP311.52
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