Time Series Prediction Based on SVM and GA

摘要：

A new time series prediction method based on support vector machine (SVM) and genetic algorithm (GA) is proposed. At first, SVM is used to partition the whole input space into several disjointed regions. Secondly, GA is adopted to determine the parameter combination of the SVM corresponding to the partitioned region obtained above. At last, the different SVM in the different input-output spaces is constructed and used to predict time series. The simulation result shows that the multiple SVM achieve significant improvement in the generalization performance in comparison with the single SVM model.

关键词： Time series Prediction Support vector machine Genetic algorithm Mixture of experts

作者: Wang Wei wei

作者单位: School of Information and Control Engineering,China University of Petroleum,Dongying 257061 China

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）