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首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics >Constructing a user-friendly GA-based fuzzy system directly from numerical data
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Constructing a user-friendly GA-based fuzzy system directly from numerical data

机译:直接从数值数据构建用户友好的基于GA的模糊系统

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摘要

This paper proposes a novel genetic algorithms (GA)-based algorithm to construct a user-friendly fuzzy system for approximating an unknown system with a satisfactory degree of accuracy. In the algorithm, the adequate number of fuzzy rules, the adequate number of membership functions of each input variable, and the parameters of membership functions will be determined automatically; in addition, the dummy input variables will be detected and discarded. Finally, several typical examples are illustrated to show the effectiveness of the algorithm.
机译:本文提出了一种新颖的基于遗传算法的算法,该算法可构建用户友好的模糊系统,以令人满意的精度逼近未知系统。在该算法中,将自动确定足够数量的模糊规则,足够数量的每个输入变量的隶属函数以及隶属函数的参数;此外,还将检测并丢弃虚拟输入变量。最后,通过几个典型的例子说明了该算法的有效性。

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