Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems

O.Cordon; F.Herrera

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Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems

机译：将遗传算法与共享方案和进化策略混合，以设计基于近似模糊规则的系统

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Genetic algorithms and evolution strategies are combined in order to build a multi-stage hybrid evolutionary algorithm for learning constrained approximate Mamdani-type knowledge bases from examples. The genetic algorithm niche concept is used in two of the three stages composing the learning process with the purposed of improving the accuracy of the designed fuzzy rule-based systems. The proposed genetic fuzzy rule-based system is used to solve an electrical engineering problem and the results obtained are compared with other methods presenting different characteristics.

机译：遗传算法和进化策略相结合，以构建一个多阶段混合进化算法，用于从示例中学习受限的近似Mamdani型知识库。在组成学习过程的三个阶段中，有两个阶段使用了遗传算法的小生境概念，目的是提高设计的基于模糊规则的系统的准确性。提出的基于遗传模糊规则的系统用于解决电气工程问题，并将获得的结果与其他具有不同特征的方法进行比较。

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《Fuzzy sets and systems》 |2001年第2期|p.235-255|共21页
作者
O.Cordon; F.Herrera;
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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类模糊数学;
关键词
Fuzzy rule-based systems; Approximate Mamdani-type knowledge bases;

机译：基于模糊规则的系统;近似Mamdani型知识库;

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2. A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems [J] . Oscar Cordon International Journal of Approximate Reasoning . 2011,第6期

机译：基于Mamdani型模糊规则的系统的进化学习方法的历史回顾：设计可解释的遗传模糊系统
3. Hybridizing rule-based power system stabilizers with genetic algorithms [J] . Abido M.A., Abdel-Magid Y.L. IEEE Transactions on Power Systems . 1999,第2期

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4. Fuzzy Partition and Input Selection by Genetic Algorithms for Designing Fuzzy Rule-Based Classification Systems [C] . Tadahiko Murata, Hisao Ishibuchi, Tomoharu Nakashima, International conference on evolutionary programming . 1998

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7. Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems [O] . O. Cordon, F. Herrera 2001

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8. Extension of the Genetic Algorithm Based Malware Strategy Evolution Forecasting Model for Botnet Strategy Evolution Modeling. [R] . Goranin, N., Cenys, A., Juknius, J. 2010

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Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems

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