Discussion about nonlinear time series prediction using least squares support vector machine

被引：0
|
作者：
Xu, RR [1 ]
Bian, GX [1 ]
Gao, CF [1 ]
Chen, TL [1 ]
机构：
[1] Nankai Univ, Dept Phys, Tianjin 300071, Peoples R China
来源：
COMMUNICATIONS IN THEORETICAL PHYSICS | 2005年 / 43卷 / 06期
关键词：
least squares support vector machine; nonlinear time series; prediction; clustering;
D O I：
暂无
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction. First, the parameter gamma 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.
引用
收藏
页码：1056 / 1060
页数：5
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