The aim of the study is to setup dynamical prediction model of complicated mechanism nonlinear motive parameters.
研究目的是建立机构复杂非线性运动参数的动态预测模型。
The result shows that the fuzzy similarity index is better than dynamical similarity index in increasing anticipation time and decreasing false prediction rate for the prediction of epileptic seizure.
分析结果表明模糊相似性指数方法能够比动态相似性指数方法获得更长的预测时间和更低的错误预测率。
A method of chaotic time series prediction problem based on local dynamical similarity is proposed.
基于混沌系统局部特征，提出了一种局部动力相似的混沌时间序列的预测方法。
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