Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5726
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dc.contributor.authorÇelikyılmaz, Aslı-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.date.accessioned2021-09-11T15:19:46Z-
dc.date.available2021-09-11T15:19:46Z-
dc.date.issued2009en_US
dc.identifier.isbn9783540899235-
dc.identifier.issn1434-9922-
dc.identifier.urihttps://doi.org/10.1007/978-3-540-89924-2_6-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5726-
dc.description.abstractThis chapter presents the results of experiments applied to benchmark and real life datasets to evaluate the performance of proposed algorithms. The results are compared to other soft computing methods of system modeling. In this chapter, performance of the proposed Fuzzy Functions approaches is analyzed against performances of other well-known soft computing methods using several datasets. Our goal is to assess prediction performance and robustness of the proposed methodologies on real life datasets under a variety of scenarios by altering system parameters using cross validation analysis. © 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.titleExperimentsen_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.startpage217en_US
dc.identifier.endpage304en_US
dc.identifier.scopus2-s2.0-64349108535en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.identifier.doi10.1007/978-3-540-89924-2_6-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ3-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.grantfulltextnone-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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