基于信息准则的局域预测法邻近点的选取方法

The neighbor point selection method for local prediction based on information criterion

基于信息准则,提出了选取局域预测法中邻近点个数的定量方法.并用此方法分析Lorenz模型生成的混沌时间序列和SantaFe时间序列竞赛的激光数据(DataA).实验结果表明用该方法选取邻近点的局域预测法的一步和多步预测性能较好,在满足预测精度较高的条件下,计算量较小.

The number of nearest neighbor points is an important parameter for the local prediction method, which has an important impact on the prediction accuracy and computation complexity of the local model. Based on the information criterion, the neighbor point selection method for the local prediction method is proposed in this paper. We illustrate this method by analyzing chaotic time series from Lorenz model and the experimental laser data- Santa Fe Data A. Simulation results show that using the proposed method to select neighbor points, the one-step and multi-step prediction accuracy of the local prediction method is good, and the computation complexity is reduced.