Study on Support Vector Machine in Calculating Steel Quenching Degree

The calculation of steel quenching degree has an important influence on real application. Steel quenching degree is influenced by chemical constitution and other many factors, which makes it difficult to be calculated accurately. Support vector machine (SVM) is a novel machine learning method based on statistical learning theory, which is powerful for solving the problems described by high dimension, small-sample and nonlinearity. In this paper, an SVM-based approach applied to calculate steel quenching degree is presented. With real data collected from Jiangyin Xingcheng Steel Work Co. Ltd., experiments show that SVM-based method is effective and superior to ANN-based method