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dc.contributor.authorRazzaghnia, T.
dc.date.accessioned2020-08-31T12:13:10Z
dc.date.available2020-08-31T12:13:10Z
dc.date.issued2009en_US
dc.identifier.citationRazzaghnia, T. (2009). Trapezoidal fuzzy data in possibility linear regression analysis. Maltepe Üniversitesi. s. 368.en_US
dc.identifier.isbn9786052124154
dc.identifier.urihttps://hdl.handle.net/20.500.12415/6132
dc.description.abstractFuzzy linear regression was proposed by Tanaka et al. [3] in 1982. Many different fuzzy regression approaches have been proposed by different researchers since then [1],[2] and also this subject has drawn much attention from more and more people concerned.and more people concerned. A fuzzy number A˜ is a convex normalized fuzzy subset of the real line R with an upper semi-continuous membership function of bounded support. Definition: A symmetric fuzzy numberA˜, denoted by A˜ = (α, c)L is defined as A˜ = L((x − α)/c),c > 0,Where α and c are the center and spread of A˜ and L(x) is a shape function of fuzzy numbers. A fuzzy regression analysis results in the following regression model:Y ˆ˜ = A˜0Xi0 + A˜1Xi1 + . . . + A˜pXip = AX˜ i i = 1, 2, . . . , n. In this paper, we aim to extended the constraints of Tanaka’s [3] model. Applied coefficients of the fuzzy regression by them is the symmetric triangular fuzzy numbers, while we try to replace it by more general asymmetric trapezoidal one. Possibility of two asymmetric trapezoidal fuzzy numbers is explained by possibility distribution. Two different models is presented and a numerical example is given in order to compare the proposed models with previous one. Error values shows advantage of the presented models with respect to constraints of Tanaka’s model. For the possibility distribution with asymmetric trapezoidal fuzzy numbers, we prove the following theorem.en_US
dc.language.isoengen_US
dc.publisherMaltepe Üniversitesien_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectTrapezoidal fuzzy numbersen_US
dc.subjectFuzzy linear regressionen_US
dc.subjectPossibility distributionen_US
dc.subjectMathematical programmingen_US
dc.titleTrapezoidal fuzzy data in possibility linear regression analysisen_US
dc.typeconferenceObjecten_US
dc.relation.journalInternational Conference of Mathematical Sciencesen_US
dc.contributor.departmentMaltepe Üniversitesi, İnsan ve Toplum Bilimleri Fakültesien_US
dc.identifier.startpage368en_US
dc.identifier.endpage369en_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.contributor.institutionauthorRazzaghnia, T.


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