Prediction and analysis of chaotic time series on the basis of support vector

被引：6
|
作者：
Li Tianliang [1 ]
He Liming [1 ]
Li Haipeng [1 ]
机构：
[1] AF Engn Univ, Engn Inst, Xian 710038, Peoples R China
来源：
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2008年 / 19卷 / 04期
关键词：
support vector machines; chaotic time series; prediction model; functionality;
D O I：
10.1016/S1004-4132(08)60157-7
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on discussion on the theories of support vector machines (SVM), an one-step prediction model for time series prediction is presented, wherein the chaos theory is incorporated. Chaotic character of the time series is taken into account in the prediction procedure; parameters of reconstruction-delay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neiglibor method, respectively. Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series.
引用
收藏
页码：806 / 811
页数：6
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