东南大学学报（英文版）2005，Vol.21Issue(2)：229-232,4.
多变量混沌时间序列局部多项式预测方法及应用
Local polynomial prediction method of multivariate chaotic time series and its application
方芬 1王海燕1
作者信息
- 1. 东南大学经济管理学院,南京,210096
- 折叠
摘要
Abstract
To improve the prediction accuracy of chaotic time series,a new method formed on the basis of local polynomial prediction is proposed.The multivariate phase space reconstruction theory is utilized to reconstruct the phase space firstly,and on its basis,a polynomial function is applied to construct the prediction model,then the parameters of the model according to the data matrix built with the embedding dimensions are estimated and a one-step prediction value is calculated.An estimate and one-step prediction value is calculated.Finally,the mean squared root statistics are used to estimate the prediction effect.The simulation results obtained by the Lorenz system and the prediction results of the Shanghai composite index show that the local polynomial prediction errors of the multivariate chaotic time series are small and its prediction accuracy is much higher than that of the univariate chaotic time series.关键词
混沌时间序列/相空间重构/局部多项式预测/证券市场Key words
chaotic time series/phase space reconstruction/local polynomial prediction/stock market分类
数理科学引用本文复制引用
方芬,王海燕..多变量混沌时间序列局部多项式预测方法及应用[J].东南大学学报（英文版）,2005,21(2):229-232,4.
