Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5187
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dc.contributorDepartment of Computing-
dc.creatorChai, J-
dc.creatorLiu, JNK-
dc.date.accessioned2014-12-11T08:23:06Z-
dc.date.available2014-12-11T08:23:06Z-
dc.identifier.isbn978-1-4577-0372-0-
dc.identifier.urihttp://hdl.handle.net/10397/5187-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Chai, J., & Liu, J. N. K. (2011). Class-based rough approximation with dominance principle. Paper presented at the Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011, 77-82. is available at http://dx.doi.org/10.1109/GRC.2011.6122571en_US
dc.subjectDecision classen_US
dc.subjectDominance principleen_US
dc.subjectMultiple criteria decision analysisen_US
dc.subjectRough set approachen_US
dc.titleClass-based rough approximation with dominance principleen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/GRC.2011.6122571-
dcterms.abstractDominance-based Rough Set Approach (DRSA), as the extension of Pawlak's Rough Set theory, is effective and fundamentally important in Multiple Criteria Decision Analysis (MCDA). In previous DRSA models, the definitions of the upper and lower approximations preserve the class unions rather than the singleton class. In this paper, we propose a new Class-based Rough Approximation with respect to different DRSA models including Classical DRSA model, VC-DRSA model and VP-DRSA model. In addition, we explore the new class-based reducts and their relations.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings : 2011 IEEE International Conference on Granular Computing, GrC 2011, Kaohsiung, Taiwan, Nov. 8-10, 2011, p. 77-82-
dcterms.issued2011-11-08-
dc.identifier.scopus2-s2.0-84863022298-
dc.identifier.rosgroupidr61689-
dc.description.ros2011-2012 > Academic research: refereed > Refereed conference paper-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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