A framework for choosing an appropriate fuzzy set extension in modeling

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dc.contributor.authorIşık, Gürkan
dc.date.accessioned2024-06-07T08:31:39Z
dc.date.available2024-06-07T08:31:39Z
dc.date.issued2022en_US
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractReal-world problems contain uncertainties. Fuzzy Set Theory (FST) is a popular approach to model these uncertainties. FST extensions (FSTEs) have been offered for better modeling of the uncertainties having different natures. It is essential to use the most suitable FSTE in modeling to achieve reasonable, reliable, and realistic results. However, FSTEs are preferred without stating a clear reason in most of the studies. This makes the quality and the reliability of the results of these studies questionable. Because, to obtain reliable models, the dynamics of the problem and environment should be well understood, the scenario should be well analyzed, and the assumptions and limitations of FSTE theories should be well known. In this study, a guiding framework for choosing the most suitable FSTE in modeling to obtain reliable, applicable, and efficient results is proposed. The framework consists of two parts: (i) conceptual analysis of the uncertainty types and FSTEs, (ii) a guiding procedure fed by the first step for deciding the most suitable FSTE. The procedure is illustrated by multiple numerical examples to make its benefits clear. Conceptual analysis and numerical examples show that some FSTEs have some advantages over the others for specific scenarios and problem types. For example, NS is more suitable than PFS for modeling the problems other than Multi-Criteria Decision-Making (MCDM). Another contribution of this study is showing that it is very important to choose the simplest possible FSTE to obtain reliable and applicable models.en_US
dc.identifier.doi10.1007/s10489-022-04244-2en_US
dc.identifier.endpage14370
dc.identifier.issn0924-669X
dc.identifier.issn1573-7497
dc.identifier.issue11
dc.identifier.scopusqualityQ2
dc.identifier.startpage14345
dc.identifier.urihttps://hdl.handle.net/20.500.12885/2245
dc.identifier.volume53
dc.identifier.wosWOS:000871297400001
dc.identifier.wosqualityQ2en_US
dc.institutionauthorIşık, Gürkan
dc.institutionauthoridhttps://orcid.org/0000-0002-5297-3109
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofAPPLIED INTELLIGENCEen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFuzzy modelingen_US
dc.subjectFuzzy set extensionsen_US
dc.subjectFuzzy set theoryen_US
dc.subjectUncertainty modelingen_US
dc.subjectReliabilityen_US
dc.titleA framework for choosing an appropriate fuzzy set extension in modelingen_US
dc.typeArticleen_US

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