GA BASED HYBRID FUZZY RULE OPTIMIZATION APPROACH FOR ELEVATOR GROUP CONTROL SYSTEM

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.author	Chen, Ta-Cheng	en_US
dc.contributor.author	Hsu, Yuan-Yong	en_US
dc.contributor.author	Lee, An-Chen	en_US
dc.contributor.author	Wang, Shiang-Yu	en_US
dc.date.accessioned	2014-12-08T15:35:17Z	-
dc.date.available	2014-12-08T15:35:17Z	-
dc.date.issued	2013	en_US
dc.identifier.issn	0315-8977	en_US
dc.identifier.uri	http://hdl.handle.net/11536/23926	-
dc.description.abstract	Elevators are the essential transportation tools in high buildings so that elevator group control system (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy rule based intelligent EGCS optimized by genetic algorithm has been proposed where the rules with the corresponding parameters are generated optimally so as to maximize service quality. The experimental results show that the performance of our approach is superior to these of traditional approaches in the literature.	en_US
dc.language.iso	en_US	en_US
dc.subject	elevator group control system	en_US
dc.subject	genetic algorithm	en_US
dc.subject	fuzzy rule	en_US
dc.title	GA BASED HYBRID FUZZY RULE OPTIMIZATION APPROACH FOR ELEVATOR GROUP CONTROL SYSTEM	en_US
dc.type	Article; Proceedings Paper	en_US
dc.identifier.journal	TRANSACTIONS OF THE CANADIAN SOCIETY FOR MECHANICAL ENGINEERING	en_US
dc.citation.volume	37	en_US
dc.citation.issue	3	en_US
dc.citation.spage	937	en_US
dc.citation.epage	947	en_US
dc.contributor.department	機械工程學系	zh_TW
dc.contributor.department	Department of Mechanical Engineering	en_US
dc.identifier.wosnumber	WOS:000332808000065	-
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