Research on support vector machine-used traffic flow patterns prediction methods

Support vector machine(SVM) is a kind of new machine learning algorithm emerged in recent years based on VC-dimension theory and structure risk minimization principle of statistical learning theory(SLT). SVM is advanced in the area of data mining and classification. To improve the accuracy and efficiency of predication about the traffic flow pattern, the method about SVM-used data classification is researched, and an appropriate model is built to predict the traffic flow patterns based on real data. Results show that this method has a high efficiency and accuracy which leads a broad application prospect.