Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5781
Full metadata record
DC FieldValueLanguage
dc.contributor.authorÇelikyılmaz, Aslı-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.date.accessioned2021-09-11T15:20:01Z-
dc.date.available2021-09-11T15:20:01Z-
dc.date.issued2009en_US
dc.identifier.isbn9783540899235-
dc.identifier.issn1434-9922-
dc.identifier.urihttps://doi.org/10.1007/978-3-540-89924-2_3-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5781-
dc.description.abstractThe new fuzzy system modeling approach based on fuzzy functions implements fuzzy clustering algorithm during structure identification of the given system. This chapter introduces foundations of fuzzy clustering algorithms and compares different types of well-known fuzzy clustering approaches. Then, a new improved fuzzy clustering approach is presented to be used for fuzzy functions approaches to re-shape membership values into powerful predictors. Lastly, two new cluster validity indices are introduced to be used to validate the improved fuzzy clustering algorithm results. © 2009 Springer-Verlag Berlin Heidelberg.en_US
dc.language.isoenen_US
dc.relation.ispartofStudies in Fuzziness and Soft Computingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleImproved Fuzzy Clusteringen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.volume240en_US
dc.identifier.startpage51en_US
dc.identifier.endpage104en_US
dc.identifier.scopus2-s2.0-64349122525en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.identifier.doi10.1007/978-3-540-89924-2_3-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ3-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Dec 21, 2024

Page view(s)

38
checked on Dec 23, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.