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首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B >A GA-based method for constructing fuzzy systems directly from numerical data
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A GA-based method for constructing fuzzy systems directly from numerical data

机译:基于GA的直接从数值数据构建模糊系统的方法

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摘要

A method based on the concepts of genetic algorithm (GA) and recursive least-squares method is proposed to construct a fuzzy system directly from some gathered input-output data of the discussed problem. The proposed method can find an appropriate fuzzy system with a low number of rules to approach an identified system under the condition that the constructed fuzzy system must satisfy a predetermined acceptable performance. In this method, each individual in the population is constructed to determine the number of fuzzy rules and the premise part of the fuzzy system, and the recursive least-squares method is used to determine the consequent part of the constructed fuzzy system described by this individual. Finally, three identification problems of nonlinear systems are utilized to illustrate the effectiveness of the proposed method.
机译:提出了一种基于遗传算法和递推最小二乘法的概念,直接从所讨论问题的一些输入输出数据中构建模糊系统。所提出的方法可以在构造的模糊系统必须满足预定的可接受性能的条件下找到具有少量规则的合适的模糊系统来接近所识别的系统。在该方法中,构造总体中的每个个体以确定模糊规则的数量和模糊系统的前提部分,然后使用递推最小二乘法确定该个体所描述的所构建的模糊系统的结果部分。最后,利用非线性系统的三个辨识问题来说明所提方法的有效性。

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