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An interval type-2 fuzzy PCM algorithm for pattern recognition

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dc.contributor.authorMin, Ji-Hee-
dc.contributor.authorShim, Eun-A-
dc.contributor.authorRhee, Frank Chung-Hoon-
dc.date.accessioned2021-06-23T15:05:47Z-
dc.date.available2021-06-23T15:05:47Z-
dc.date.created2021-02-18-
dc.date.issued2009-08-
dc.identifier.issn1098-7584-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/40984-
dc.description.abstractThe Possibilistic C-means (PCM) was proposed to overcome some of the drawbacks associated with the Fuzzy C-means (FCM) such as improved performance for noise data. However, PCM possesses some drawbacks such as sensitivity in the initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome theses drawbacks, we propose an interval type-2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm. ©2009 IEEE.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-
dc.titleAn interval type-2 fuzzy PCM algorithm for pattern recognition-
dc.typeArticle-
dc.contributor.affiliatedAuthorRhee, Frank Chung-Hoon-
dc.identifier.doi10.1109/FUZZY.2009.5277167-
dc.identifier.scopusid2-s2.0-71249101581-
dc.identifier.wosid000274242600084-
dc.identifier.bibliographicCitationIEEE International Conference on Fuzzy Systems, pp.480 - 483-
dc.relation.isPartOfIEEE International Conference on Fuzzy Systems-
dc.citation.titleIEEE International Conference on Fuzzy Systems-
dc.citation.startPage480-
dc.citation.endPage483-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryMathematics, Applied-
dc.subject.keywordAuthorFuzzy C-means-
dc.subject.keywordAuthorPossibilistic c-means-
dc.subject.keywordAuthorFuzzy approach-
dc.subject.keywordAuthorFuzzy parameter-
dc.subject.keywordAuthorPattern recognition-
dc.subject.keywordAuthorInitial parameter-
dc.subject.keywordAuthorShort distances-
dc.subject.keywordAuthorPulse code modulation-
dc.subject.keywordAuthorNoise data-
dc.subject.keywordAuthorFuzzy systems-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/5277167?arnumber=5277167&SID=EBSCO:edseee-
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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