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Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/70001
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dc.titleDNA coded GA for the rule base optimization of a fuzzy logic controller
dc.contributor.authorPeng, X.
dc.contributor.authorVadakkepat, P.
dc.contributor.authorTong Heng Lee
dc.date.accessioned2014-06-19T03:07:04Z
dc.date.available2014-06-19T03:07:04Z
dc.date.issued2001
dc.identifier.citationPeng, X.,Vadakkepat, P.,Tong Heng Lee (2001). DNA coded GA for the rule base optimization of a fuzzy logic controller. Proceedings of the IEEE Conference on Evolutionary Computation, ICEC 2 : 1191-1196. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/70001
dc.description.abstractA DNA coded genetic-algorithm (GA) is proposed to optimize the rule-base of a fuzzy logic controller (FLC). The controller is designed for a vehicle-active suspension system to improve the driving comfort. The DNA coded GA constructed optimal decision-making rules for the fuzzy logic controller. Simulation results demonstrated the effectiveness of the algorithm.
dc.sourceScopus
dc.subjectDNA
dc.subjectDNA coded GA
dc.subjectFuzzy logic controller and active suspension system
dc.subjectGenetic algorithm
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleProceedings of the IEEE Conference on Evolutionary Computation, ICEC
dc.description.volume2
dc.description.page1191-1196
dc.identifier.isiutNOT_IN_WOS
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