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On the selection of input variables by using the GA for the estimation of multi-dimensional chaotic dynamics based upon the multi-stage fuzzy inference systems

机译:基于多级模糊推理系统的遗传算法估计多维混沌动力学的输入变量选择

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摘要

This report deals with the selection of input variables by using the GA for the estimation of multi-dimensional chaotic dynamics based upon the multi-stage fuzzy inference systems. Inthe desing of multi-stage fuzzy inference systems, we usually use very small number of rules, and the system is applicable to the system identification using many input variables. It is necessary to determine optimal sets of input variable to the fuzzy inference system by which we analyze the structure of the chaotic dynamics. In the report, we utilize the GA to determine the optimal selection of input variables for the multi-stage fuzzy inference systems, as well as the GA application for the optimization of shapes of membership functions.
机译:本报告通过基于多级模糊推理系统的遗传算法估计多维混沌动力学,使用遗传算法处理输入变量的选择。在多阶段模糊推理系统的设计中,我们通常使用很少的规则,并且该系统适用于使用许多输入变量的系统识别。有必要确定模糊推理系统的输入变量的最佳集合,以此来分析混沌动力学的结构。在报告中,我们利用遗传算法为多级模糊推理系统确定输入变量的最佳选择,并利用遗传算法来优化隶属函数的形状。

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