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Variable precision multi decision λ-soft dominance based rough sets and their applications in conflict problems

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dc.contributor.authorRehman, Noor-
dc.contributor.authorAli, Abbas-
dc.contributor.authorShah, Syed Inayat Ali-
dc.contributor.authorAli, Muhammad Irfan-
dc.contributor.authorPark, Choonkil-
dc.date.accessioned2022-07-09T14:02:43Z-
dc.date.available2022-07-09T14:02:43Z-
dc.date.created2021-05-12-
dc.date.issued2019-06-
dc.identifier.issn1064-1246-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147639-
dc.description.abstractThe extension of rough set model is a crucial and vast research direction in rough set theory. Meanwhile decision making can be considered as a mental process in which human beings make a choice among several alternatives. However, with the increasing complexity of real decision making problems, the decision makers frequently face the challenge of characterizing their preferences in an uncertain context. In the present paper, we initiate a multi attribute group decision making problem in the presence of multi attribute and multi decision in decision making with preferences. We further present the concept of soft preference relation and soft dominance relation corresponding to decision attribute in the multi criteria and multi decision information system. Further we present the idea of variable precision multi decision soft dominance based rough set model and their applications in solving a multi agent conflict analysis decision problem. The proposed method addresses the limitations of the Pawlak's model and Sun's conflict analysis model and thus improve these models. Finally, the results on labor management negotiation problems show that the proposed algorithms are more effective and efficient for feasible consensus strategy when compared with other techniques.-
dc.language영어-
dc.language.isoen-
dc.publisherIOS PRESS-
dc.titleVariable precision multi decision λ-soft dominance based rough sets and their applications in conflict problems-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Choonkil-
dc.identifier.doi10.3233/JIFS-191197-
dc.identifier.scopusid2-s2.0-85067600735-
dc.identifier.wosid000471893900018-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT & FUZZY SYSTEMS, v.36, no.6, pp.5345 - 5360-
dc.relation.isPartOfJOURNAL OF INTELLIGENT & FUZZY SYSTEMS-
dc.citation.titleJOURNAL OF INTELLIGENT & FUZZY SYSTEMS-
dc.citation.volume36-
dc.citation.number6-
dc.citation.startPage5345-
dc.citation.endPage5360-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusFUZZY-SETS-
dc.subject.keywordPlusPREFERENCE-RELATION-
dc.subject.keywordPlusAPPROXIMATION-
dc.subject.keywordPlusATTRIBUTES-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorRough set-
dc.subject.keywordAuthorsoft set-
dc.subject.keywordAuthorpreference relation-
dc.subject.keywordAuthorinclusion degree-
dc.subject.keywordAuthorsoft preference relation-
dc.identifier.urlhttps://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs191197-
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