ARTIFICIAL NEURAL NETWORK AND ENTROPY APPROACH IN FUZZY NONLINEAR REGRESSION

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dc.authorid0000-0002-9840-0461en_US
dc.authorid0000-0003-4094-7664en_US
dc.date.accessioned2020-12-15T13:02:31Z
dc.date.available2020-12-15T13:02:31Z
dc.date.issued2012en_US
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractFuzzy nonlinear regression (FNR) is different from classic regression models just because its output consists of fuzzy numbers. Predictions are realized by FNR models for the cases in which both input variables are nonlinearly related and output variable is fuzzy. Besides, a FNR model may be used to construct a probability interval for the output variable precisely. It is important to note that an entropy-based approach to FNR models results in smaller propagations for fuzzy intervals.en_US
dc.description.abstractFuzzy nonlinear regression (FNR) is different from classic regression models just because its output consists of fuzzy numbers. Predictions are realized by FNR models for the cases in which both input variables are nonlinearly related and output variable is fuzzy. Besides, a FNR model may be used to construct a probability interval for the output variable precisely. It is important to note that an entropy-based approach to FNR models results in smaller propagations for fuzzy intervals.en_US
dc.identifier.citationKahraman, U. M., Evren, A. (2012). Artıfıcıal Neural Network and Entropy Approach ın Fuzzy Nonlınear Regressıon. Journal of Selcuk University Natural and Applied Science, 1, (1), 14-29.en_US
dc.identifier.endpage29en_US
dc.identifier.issn2147-3781en_US
dc.identifier.issue1en_US
dc.identifier.startpage14en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/40782
dc.identifier.volume1en_US
dc.institutionauthorKahraman, Umran Munıre
dc.institutionauthorEvren, Atif
dc.language.isotren_US
dc.publisherSelçuk Üniversitesien_US
dc.relation.ispartofJournal of Selcuk University Natural and Applied Scienceen_US
dc.relation.publicationcategoryMakale - Ulusal - Editör Denetimli Dergien_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectNonlinear regressionen_US
dc.subjectNonlinear regressionen_US
dc.subjectneural networksen_US
dc.subjectneural networksen_US
dc.subjectfuzzy set theoryen_US
dc.subjectfuzzy set theoryen_US
dc.subjectentropy approachen_US
dc.subjectentropy approachen_US
dc.titleARTIFICIAL NEURAL NETWORK AND ENTROPY APPROACH IN FUZZY NONLINEAR REGRESSIONen_US
dc.typeArticleen_US

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