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An Extended Evolutionary Approach Toward Optimal Design of Fuzzy Systems

机译:模糊系统最优设计的扩展进化方法

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This paper proposes an extended evolutionary approach in which genetic algorithms and hierarchical modules are used to automatically design fuzzy systems. The basic idea is to define fuzzy system parameters and operators, organized in hierarchical modules which interact in a evolutionary process to produce, at the final generation, a fuzzy system behavior close to the optimal desired one. In this work, besides the automatic definition of some important parameters, like number of fuzzy rules and shape of membership functions, the inference mechanism may also be obtained through evolution. Some intrinsic characteristics of fuzzy systems concerning function approximation are analyzed and simulation examples are carried out to attest the efficiency of the automatic design process.
机译:本文提出了一种扩展的进化方法,其中遗传算法和分级模块用于自动设计模糊系统。基本思想是定义模糊系统参数和操作员,在进行进化过程中的分层模块中组织,以在最终一代产生靠近最佳所需的模糊系统行为。在这项工作中,除了一些重要参数的自动定义之外,与隶属函数的模糊规则和形状相同,也可以通过演进来获得推理机制。分析了有关功能近似的模糊系统的一些内在特征,并进行了模拟实施例以证明自动设计过程的效率。

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