GA BASED HYBRID FUZZY RULE OPTIMIZATION APPROACH FOR ELEVATOR GROUP CONTROL SYSTEM
| dc.citation.epage | 947 | en_US |
| dc.citation.issue | 3 | en_US |
| dc.citation.spage | 937 | en_US |
| dc.citation.volume | 37 | en_US |
| 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.contributor.department | 機械工程學系 | zh_TW |
| dc.contributor.department | Department of Mechanical Engineering | 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.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.identifier.issn | 0315-8977 | en_US |
| dc.identifier.journal | TRANSACTIONS OF THE CANADIAN SOCIETY FOR MECHANICAL ENGINEERING | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/23926 | |
| dc.identifier.wosnumber | WOS:000332808000065 | |
| 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 |
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