说明：  混沌时间序列局域法多步预报模型.doc(有程序下载) 针对混沌时间序列预测中用加权一阶局域法单步预报模型进行多步预报时计算量大且存在误差累积效应的不足，本文提出了基于相空间重构技术的局域法多步预报模型，包括加权一阶局域法多步预报模型和RBF神经网络多步预报模型。对几种典型混沌序列的预测仿真表明，两种模型对混沌时间序列的多步预报均较有效。
(chaotic time series Local Law multi-step prediction model. Doc (with the download) against chaotic time series prediction using a weighted-Local law single-step prediction model multi-step forecast at large calculation error and the cumulative effect of the shortage, In this paper, based on the phase-space reconstruction of local law multi-step prediction model Weighted including a local law-order multi-step prediction model and RBFNN multi-step prediction model. Several typical of the chaotic sequence forecast simulation shows that the two models of chaotic time series multi-step prediction than effective.)