中国物理B ›› 2007, Vol. 16 ›› Issue (11): 3220-3225.doi: 10.1088/1009-1963/16/11/013

• GENERAL • 上一篇    下一篇

The improved local linear prediction of chaotic time series

孟庆芳, 彭玉华, 孙佳   

  1. School of Information Science and Engineering, Shandong University, Jinan 250100, China
  • 出版日期:2007-11-20 发布日期:2007-11-20

The improved local linear prediction of chaotic time series

Meng Qing-Fang(孟庆芳)†, Peng Yu-Hua(彭玉华), and Sun Jia(孙佳)   

  1. School of Information Science and Engineering, Shandong University, Jinan 250100, China
  • Online:2007-11-20 Published:2007-11-20

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摘要： Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time series and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.

Abstract: Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time series and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.

Key words: local linear prediction, Bayesian information criterion, state space reconstruction, chaotic time series

中图分类号:  (Time series analysis)

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