SVM Regression Modeling Based on Properties of Engineering Materials with PLS Feature Extraction

A combination regression algorithm of PLS-SVM is proposed for the properties of engineering materials. The algorithm first extracts the feature from the primal sample sets by PLS, and then carries out SVM regression estimation using the new sample sets attained. Thus the algorithm will have the ability of extracting feature. The simulation results indicate that the new combined SVM regression algorithm can effectively solve the regression estimation problem including dimensions reduction, noise elimination and multiple correlations between independent variables. The algorithm has good and wide application foreground in research of properties of engineering materials.