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dc.contributor.authorPrasad, M.en_US
dc.contributor.authorChou, K. P.en_US
dc.contributor.authorSaxena, A.en_US
dc.contributor.authorKawrtiya, O. P.en_US
dc.contributor.authorLi, D. L.en_US
dc.contributor.authorLin, C. T.en_US
dc.date.accessioned2017-04-21T06:49:56Z-
dc.date.available2017-04-21T06:49:56Z-
dc.date.issued2014en_US
dc.identifier.isbn978-1-4799-4530-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/136144-
dc.description.abstractThis paper demonstrates a novel model for Mamdani type fuzzy inference system by using the knowledge learning ability of collaborative fuzzy clustering and rule learning capability of FCM. The collaboration process finds consistency between different datasets, these datasets can be generated at various places or same place with diverse environment containing common features space and bring together to find common features within them. For any kind of collaboration or integration of datasets, there is a need of keeping privacy and security at some level. By using collaboration process, it helps fuzzy inference system to define the accurate numbers of rules for structure learning and keeps the performance of system at satisfactory level while preserving the privacy and security of given datasets.en_US
dc.language.isoen_USen_US
dc.subjectfuzzy c-means (FCM)en_US
dc.subjectcollaborative fuzzy clustering (CFC)en_US
dc.subjectstructure learningen_US
dc.subjectcollaboration processen_US
dc.subjectfuzzy inference systemen_US
dc.subjectprivacy and securityen_US
dc.titleCollaborative Fuzzy Rule Learning for Mamdani Type Fuzzy Inference System with Mapping of Cluster Centersen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)en_US
dc.citation.spage15en_US
dc.citation.epage20en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000380587600003en_US
dc.citation.woscount0en_US
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