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Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine 被引量:3
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作者 XURui-Rui BIANGuo-Xin GAOChen-Feng CHENTian-Lun 《Communications in Theoretical Physics》 SCIE CAS CSCD 2005年第6期1056-1060,共5页
The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction.First, the parameter γ and multi-step prediction capabilities of the LS-SVM network are discussed. Then we emplo... The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction.First, the parameter γ and multi-step prediction capabilities of the LS-SVM network are discussed. Then we employ clustering method in the model to prune the number of the support values. The learning rate and the capabilities of filtering noise for LS-SVM are all greatly improved. 展开更多
关键词 非线性时间序列预测 支持矢量机器 统计学习 结构风险 最小方差
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