Material erosion rate model based on PCLS-SVM

Support vector machine (SVM) is a novel machine learning method based on statistical learning theory. A material erosion rate model based on principal component least square SVM (PCLS-SVM) is proposed. PCA calculates principal components in high dimensional feature space and reduces dimensions of sample. Cross validation method is used to select parameters of PCLS-SVM model. PCLS-SVM is applied to prediction of material erosion rate. Results indicate that this method features high learning speed and well generalization ability.