Hybrid least-squares regression modelling using confidence bounds

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dc.authorscopusid14619912500
dc.authorscopusid7004385524
dc.contributor.authorTütmez B.
dc.contributor.authorKaymak U.
dc.date.accessioned2024-08-04T20:02:24Z
dc.date.available2024-08-04T20:02:24Z
dc.date.issued2013
dc.departmentİnönü Üniversitesien_US
dc.description.abstractOne of the questions regarding bridging of soft computing and statistical methods is the (re-)use of information between the two approaches. In this context, we consider in this paper whether statistical confidence bounds can be used in the hybrid fuzzy least squares regression problem. By using the confidence limits as the spreads of the fuzzy numbers, uncertainty estimates for the fuzzy model can be provided. Experiments have been conducted in the paper, both on regression coefficients and the predicted responses of regression models. The findings show that the use of the confidence intervals as the widths of memberships gives successful results and opens new possibilities in system modeling and analysis. © Springer-Verlag 2013.en_US
dc.identifier.doi10.1007/978-3-642-30278-7_5
dc.identifier.endpage63en_US
dc.identifier.issn1434-9922
dc.identifier.scopus2-s2.0-84891687773en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage53en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-642-30278-7_5
dc.identifier.urihttps://hdl.handle.net/11616/91646
dc.identifier.volume285en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofStudies in Fuzziness and Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keyword]en_US
dc.titleHybrid least-squares regression modelling using confidence boundsen_US
dc.typeReview Articleen_US

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