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dc.contributor.authorŞentürk, Sevil
dc.contributor.editorRuan, D
dc.contributor.editorMontero, J
dc.contributor.editorLu, J
dc.date.accessioned2019-10-20T09:31:31Z
dc.date.available2019-10-20T09:31:31Z
dc.date.issued2008
dc.identifier.isbn978-981-279-946-3
dc.identifier.urihttps://dx.doi.org/10.1142/9789812799470_0158
dc.identifier.urihttps://hdl.handle.net/11421/17718
dc.description8th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science -- SEP 21-24, 2008 -- Madrid, SPAINen_US
dc.descriptionWOS: 000259061900158en_US
dc.description.abstractThe fuzzy set theory is a powerful method to analyze the statistical data which includes ambiguity or vague comes from the structure of the process, measurement systems or environmental conditions. Crisp value collected process can transform the fuzzy numbers (a,b,c) by using the membership functions and calculate fuzzy control limits by using the traditional control limits equations. Thus, the flexibility on control limits can be achieved by analyzing the process like "in-control" or "out of control". The regression control chart is used especially to evaluate the tool wearing problem in industry. In the traditional regression control chart, all data assume crisp value. With fuzzy set theory, the fuzzy regression control chart can be handled based on a-cuts approach by using the fuzzy midrange transformation techniques. In this study, the theoretical structure of alpha-level fuzzy midrange for a-cuts for fuzzy X-regression control charts and fuzzy (R) over tilde control chart are proposed.en_US
dc.description.sponsorshipComplutense Univ, Belgian Nucl Res Ctr, Ghent Univ, Govt Spainen_US
dc.language.isoengen_US
dc.publisherWorld Scientific Publ Co Pte LTDen_US
dc.relation.ispartofseriesWorld Scientific Proceedings Series on Computer Engineering and Information Science
dc.relation.isversionof10.1142/9789812799470_0158en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleFuzzy regression control charten_US
dc.typeconferenceObjecten_US
dc.relation.journalComputational Intelligence in Decision and Controlen_US
dc.contributor.departmentAnadolu Üniversitesi, Fen Fakültesi, İstatistik Bölümüen_US
dc.identifier.volume1en_US
dc.identifier.startpage963en_US
dc.identifier.endpage968en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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