Application of Support Vector Machine to Prediction of Chaotic Systems
支持向量机在混沌系统预测中的应用*

Support Vector Machine(SVM) regression method is proposed for solving the prediction problem of chaotic systems.The algorithm of SVM regression is formulated. One application is given to the prediction of four-order chaotic time series.Based on this application and in conjunction with the chaotic characteristics of urban traffic,another application is given to the real-time prediction of the traffic flow in Zhuhai city.Simulation experiments show that SVM regression has fast learning ability and good generalization.It is very suitable for the prediction of chaotic time series,and is also effective to forecast urban traffic flow.