电子学报 ›› 2006, Vol. 34 ›› Issue (10): 1929-1932.

• 论文 • 上一篇    下一篇

基于组合SVR的非平稳时间序列的模糊建模方法

林树宽, 支力佳, 张少敏, 乔建忠, 王国仁, 于 戈   

  1. 东北大学信息科学与工程学院,辽宁沈阳 110004
  • 收稿日期:2005-10-11 修回日期:2006-07-03 出版日期:2006-10-25 发布日期:2006-10-25

A Multi-SVR Based Fuzzy Modeling Method for Non-Stationary Time Series

LIN Shu-kuan, ZHI Li-jia, ZHANG Shao-min, QIAO Jian-zhong, WANG Guo-ren, YU Ge   

  1. College of Information Science and Engineering,Northeastern University,Shenyang,Liaoning 110004,China
  • Received:2005-10-11 Revised:2006-07-03 Online:2006-10-25 Published:2006-10-25

摘要: 本文介绍一种对非平稳时间序列建模的新方法.参考Janos Abonyi提出的应用于时间序列的模糊分块算法,将该算法与改进的支持向量回归模型结合起来.首先,提出一种改进的支持向量回归的表达形式;然后,通过启发式的加权方法将模糊分块的信息与SVR结合起来;最后,提出一种基于组合SVR的建模方法.实验结果表明,本文提出的方法对于非平稳时间序列的建模具有较高的实用价值.

关键词: 非平稳时间序列, 模糊分块, 启发式的ε加权方法, 组合支持向量回归

Abstract: A new approach for modeling non-stationary time series was introduced in this paper.Combine the fuzzy segmentation which was proposed by Janos Abonyi with Support Vector Machines(SVMs).Firstly,a modified Support Vector Regression(SVR) was proposed;Secondly,fuzzy segment information was combined with SVR by heuristic weighting method;Thirdly,we discussed a model based on multi-SVR.Experimental results show that the method proposed in this paper has great practical values for non-stationary time series modeling.

Key words: non-stationary time series, fuzzy segmentation, heuristic weighting method, multi support vector regression

中图分类号: