基于操作进化调优的模糊If-Then规则库优化

2009 39th International Symposium on Multiple-Valued Logic Pub Date : 2009-05-21 DOI:10.1109/ISMVL.2009.39

C. Moraga, M. Sugeno, E. Trillas

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引用次数: 7

摘要

本文讨论了模糊if-then规则库的优化问题，方法是对使用规则的操作进行演化调整。操作的调整首先通过使用收缩函数或顺序自同构对操作进行参数化，然后对参数进行演化调整。详细讨论了基于Takagi-Sugeno规则的系统优化及其分布式实现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimization of Fuzzy If-Then Rule Bases by Evolutionary Tuning of the Operations

This paper discusses optimization of fuzzy if-then rule bases by an evolutionary adjustment of the operations considered to use the rules. Adjustment of the operations is made by first parameterizing the operations with the help of either a contracting function or an order automorphism, followed by evolutionary tuning of the parameters. Optimization of a system based on Takagi-Sugeno rules and its distributed implementation are discussed in detail.

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2009 39th International Symposium on Multiple-Valued Logic

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