中国机械工程2011，Vol.22Issue(21)：2572-2576,5.
基于粒子群优化的最小二乘支持向量机在时间序列预测中的应用
LSSVM Based on PSO and Its Applications to Time Series Prediction
摘要
Abstract
In order to improve the generalization performance and prediction accuracy of LSSVM based time series prediction,a PSO based LSSVM was studied.Firstly,a certain number of LSSVMs were trained by using training samples and then cross-validation error was applied to evaluate the generalization performance of the LSSVMs.Finally,PSO was applied to search for the optimal LSSVM with the smallest cross-validation error.Experiments on time series prediction indicate that LSSVM optimized by PSO has better prediction performance than that not optimized and conventional prediction methods.关键词
最小二乘支持向量机/粒子群优化/交叉验证/时间序列预测Key words
least square support vector machine（LSSVM）/particle swarm optimization（PSO）/cross-validation/time series prediction分类
信息技术与安全科学引用本文复制引用
张弦,王宏力..基于粒子群优化的最小二乘支持向量机在时间序列预测中的应用[J].中国机械工程,2011,22(21):2572-2576,5.
