An implementation of genetic-based learning classifier system on a wet clutch system
نویسندگان
چکیده
As a methodology for search and optimization, Genetic Algorithms (GA) has now reached a mature stage. An interesting application of GA is to use it as a rule discovery system inside a Learning Classifier System (LCS), especially in a strength-based system (zero level classifier system, ZCS). An LCS is a good solution for some complex problems. But when facing multiple objectives, the conventional LCS will have difficulties in selecting classifier since the inside rule discovery system (GA) will need a certain population size for evolution diversity. In this paper, a new genetic-based LCS with integrated Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is suggested to solve such problem. The LCS is implemented on a wet clutch system for achieving different engagement performance.
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