Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5717
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dc.contributor.authorÇelikyılmaz, Aslı-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.date.accessioned2021-09-11T15:19:44Z-
dc.date.available2021-09-11T15:19:44Z-
dc.date.issued2007en_US
dc.identifier.citation11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007, 14 May 2007 through 17 May 2007, Toronto, 71080en_US
dc.identifier.isbn9783540725299-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://doi.org/10.1007/978-3-540-72530-5_14-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5717-
dc.description.abstractFuzzy System Models (FSM), as one of the constituents of soft computing methods, are used for mining implicit or unknown knowledge by approximating systems using fuzzy set theory. The undeniable merit of FSM is its inherent ability of dealing with uncertain, imprecise, and incomplete data and still being able to make powerful inferences. This paper provides an overview of FSM techniques with an emphasis on new approaches on improving the prediction performances of system models. A short introduction to soft computing methods is provided and new improvements in FSMs, namely, Improved Fuzzy Functions (IFF) approaches is reviewed. IFF techniques are an alternate representation and reasoning schema to Fuzzy Rule Base (FRB) approaches. Advantages of the new improvements are discussed. © Springer-Verlag Berlin Heidelberg 2007.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData miningen_US
dc.subjectFuzzy systemsen_US
dc.subjectKnowledge discoveryen_US
dc.subjectSoft computingen_US
dc.titleEvolution of Fuzzy System Models: an Overview and New Directionsen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.volume4482 LNAIen_US
dc.identifier.startpage119en_US
dc.identifier.endpage126en_US
dc.identifier.scopus2-s2.0-38048999559en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.identifier.doi10.1007/978-3-540-72530-5_14-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007en_US
dc.identifier.scopusqualityQ2-
item.openairetypeConference Object-
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
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