A cascaded genetic algorithm for improving fuzzy-system design

Abstract We present a cascaded genetic algorithm which automatically generates high-performance fuzzy systems with a minimal number of fuzzy sets and rules. Such a tool is especially useful for complex systems which can no longer be designed and optimized manually. The cascade technique is tested on a fuzzy controller design task. Experimental results show that the proposed algorithm yields considerably better results than a conventional genetic algorithm.

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