Study on the Predictable Size of Chaotic Time Series Based on n-rank Average Divergence Degree
Cheng Guo-ping · Acta Simulata Systematica Sinica · 2004
The method of determining predictable size of chaotic time series based on maximal Lyapunov exponent is deeply analyzed, and its defect is also pointed out. On this basis, a novel method used for the determination of predictable size based on n-rank average divergence degree is proposed. Firstly, the definition of n-rank average divergence degree is given. Then, the principle of the new method is demonstrated, and its computing procedure is also summarized. Finally, the suggested method is applied to the predictable size determination of power load time series, and by means of analyzing and comparing the forecast error, the validity of this method is verified.