计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (35): 61-64.

• 学术探讨 • 上一篇    下一篇

混沌时间序列改进的加权一阶局域预测法

孟庆芳,彭玉华   

  1. 山东大学 信息科学与工程学院,济南 250100
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-11 发布日期:2007-12-11
  • 通讯作者: 孟庆芳

Improved adding weight first order local prediction method for chaotic time series

MENG Qing-fang,PENG Yu-hua   

  1. School of Information Science and Engineering,Shandong University,Ji’nan 250100,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-11 Published:2007-12-11
  • Contact: MENG Qing-fang

摘要: 加权一阶局域预测法是目前最常用的一种混沌时间序列预测方法。基于延迟坐标相空间重构理论,提出了混沌时间序列改进的加权一阶局域预测法。仿真结果表明该方法的多步预测性能与一步预测性能明显好于加权一阶局域预测法的多步预测性能与一步预测性能。

关键词: 加权一阶局域预测法, 相空间重构, 混沌时间序列

Abstract: Adding weight first order local prediction method is the most usually used method to predict chaotic time series.Based on phase space delay-coordinate reconstruction of a chaotic dynamics system,an improved adding weight first order local prediction method is proposed to predict chaotic time series in this paper.Simulation results show that the improved 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 method are superior to those of the adding weight first order local prediction method.

Key words: adding weight first order local prediction method, phase space reconstruction, chaotic time series