Statistical modelling of mechanical properties of microalloyed steels by application of artificial neural networks

被引：11

作者：

Dumortier, C

Lehert, P

Krupa, P

Charlier, A

机构：

[1] Fac Polytech Mons, Dept Met, B-7000 Mons, Belgium

[2] Catholic Univ Mons, Data Processing Dept, B-7000 Mons, Belgium

[3] Cockerill Sambre, Dept Comp, B-6090 Couillet, Belgium

[4] Cockerill Sambre, R&D Corp, CDAM, B-4400 Flemalle, Belgium

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MICROALLOYING IN STEELS | 1998年 / 284-2卷

关键词：

microalloyed steel; mechanical properties; statistical modelling; artificial neural networks; stepwise multiple regression; principal components analysis;

D O I：

10.4028/www.scientific.net/MSF.284-286.393

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Neural Networks have been used to determine mechanical properties of microalloyed steels produced at Cockerill Sambre Steel Plant. By comparison with multiple linear regression, this method presents the advantage of dealing with non-linearity effects and to detect easily possible interactions between the predictors. However, statistical multivariate techniques continue to be an interesting tool to improve the quality of the prediction and to explain the results of the modelling.

引用

页码：393 / 400

页数：8

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