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https://hdl.handle.net/20.500.11851/5717
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Çelikyılmaz, Aslı | - |
dc.contributor.author | Türkşen, İsmail Burhan | - |
dc.date.accessioned | 2021-09-11T15:19:44Z | - |
dc.date.available | 2021-09-11T15:19:44Z | - |
dc.date.issued | 2007 | en_US |
dc.identifier.citation | 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007, 14 May 2007 through 17 May 2007, Toronto, 71080 | en_US |
dc.identifier.isbn | 9783540725299 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://doi.org/10.1007/978-3-540-72530-5_14 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/5717 | - |
dc.description.abstract | Fuzzy 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.iso | en | en_US |
dc.publisher | Springer Verlag | en_US |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Data mining | en_US |
dc.subject | Fuzzy systems | en_US |
dc.subject | Knowledge discovery | en_US |
dc.subject | Soft computing | en_US |
dc.title | Evolution of Fuzzy System Models: an Overview and New Directions | en_US |
dc.type | Conference Object | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Industrial Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 4482 LNAI | en_US |
dc.identifier.startpage | 119 | en_US |
dc.identifier.endpage | 126 | en_US |
dc.identifier.scopus | 2-s2.0-38048999559 | en_US |
dc.institutionauthor | Türkşen, İsmail Burhan | - |
dc.identifier.doi | 10.1007/978-3-540-72530-5_14 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.relation.conference | 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007 | en_US |
dc.identifier.scopusquality | Q2 | - |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | Endüstri Mühendisliği Bölümü / Department of Industrial Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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