Dimension-exponent Adding-weight One-rank Local-region Method for Prediction of Chaotic Time Series
A novel dimension-exponent adding-weight one-rank local-region method is introduced in this paper. An index form attenuation factor composed of the product of the largest Lyapunov exponent and the delay time corresponding to each dimension of the adjacent point, is applied to amend the vector distance formula of original method. The revised distance formula not only expresses different relevance of each phase points and the center point, but also the correlation between each dimension of this phase points and the first dimension of the center point. The Logistic chaotic time series are forecasted using this improved method, the results show that the prediction accuracy is improved in the proposed method compared to the original one. Besides, the more chaotic the time series is, and the greater the embedding dimension is, the more obvious the improving effectiveness is.
adding-weight one-rank local-region methodthe largest Lyapunov exponentchaotic time seriesprediction
国家科技期刊平台
NSTL
万方数据
维普
