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Multi-SVR based fuzzy modeling method for non-stationary time series

  • Shu Kuan Lin*
  • , Li Jia Zhi
  • , Shao Min Zhang
  • , Jian Zhong Qiao
  • , Guo Ren Wang
  • , Ge Yu
  • *此作品的通讯作者
  • Northeastern University China

科研成果: 期刊稿件文章同行评审

摘要

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.

源语言英语
页(从-至)1929-1932
页数4
期刊Tien Tzu Hsueh Pao/Acta Electronica Sinica
34
10
出版状态已出版 - 10月 2006
已对外发布

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