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dc.contributor.authorCheng, CHen_US
dc.contributor.authorChang, JRen_US
dc.contributor.authorHo, THen_US
dc.contributor.authorChen, APen_US
dc.date.accessioned2014-12-08T15:36:38Z-
dc.date.available2014-12-08T15:36:38Z-
dc.date.issued2005en_US
dc.identifier.isbn3-540-27871-0en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/24978-
dc.description.abstractThe OWA (Ordered Weighted Averaging) aggregation operators have been extensively adopted to assign the relative weights of numerous criteria. However, previous aggregation operators (including OWA) are independent of aggregation situations. To solve the problem, this study proposes a new aggregation model - dynamic fuzzy OWA operators based on situation model, which can modify the associated dynamic weight based on the aggregation situation and can work like a "magnifying lens" to enlarge the most important attribute dependent on minimal information, or can obtain equal attribute weights based on maximal information. We also apply proposed model to evaluate the service quality of airline.en_US
dc.language.isoen_USen_US
dc.titleEvaluating the airline service quality by fuzzy OWA operatorsen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.journalMODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE, PROCEEDINGSen_US
dc.citation.volume3558en_US
dc.citation.spage77en_US
dc.citation.epage88en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000231113900009-
Appears in Collections:Conferences Paper