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

作     者：Li Tianliang He Liming Li Haipeng 

作者机构：The Engineering Inst. Air Force Engineering Univ. Xi'an 710038 P. R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2008年第19卷第4期

页      面：806-811页

核心收录：

学科分类：07[理学] 08[工学] 070104[理学-应用数学] 0835[工学-软件工程] 0802[工学-机械工程] 0701[理学-数学] 080201[工学-机械制造及其自动化] 

主　　题：support vector machines chaotic time series prediction model functionality 

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-detay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neighbor method, respectively. Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series.