Uncertain fuzzy clustering: Insights and recommendations
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rhee, Frank Chung-Hoon | - |
dc.date.accessioned | 2021-06-23T20:04:24Z | - |
dc.date.available | 2021-06-23T20:04:24Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2007-02 | - |
dc.identifier.issn | 1556-603X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/43892 | - |
dc.description.abstract | Interval type-2 fuzzy sets were used to model the uncertainty that is associated with the various parameters in objective function-based clustering. The purpose was to represent and manage the uncertainty in the cluster memberships by incorporating interval type-2 fuzzy sets. As a result, interval type-2 clustering methods were obtained by modifying the prototype-updating and hard-partitioning procedures in the type-1 fuzzy objective function-based clustering. As a consequence, the management of uncertainty by an interval type-2 fuzzy approach aids cluster prototypes to converge to a more desirable location than a type-1 fuzzy approach. Several examples illustrated the effectiveness of interval type-2 fuzzy approach methods. Furthermore, the uncertainty associated with the parameters for other existing clustering algorithms can be considered in the development of several other interval type-2 clustering algorithms. They are currently under investigation. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Uncertain fuzzy clustering: Insights and recommendations | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Rhee, Frank Chung-Hoon | - |
dc.identifier.doi | 10.1109/MCI.2007.357193 | - |
dc.identifier.scopusid | 2-s2.0-34248141805 | - |
dc.identifier.wosid | 000246616500005 | - |
dc.identifier.bibliographicCitation | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, v.2, no.1, pp.44 - 56 | - |
dc.relation.isPartOf | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | - |
dc.citation.title | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | - |
dc.citation.volume | 2 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 44 | - |
dc.citation.endPage | 56 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/4195041/ | - |
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