A novel picture fuzzy CRITIC & REGIME methodology: Wearable health technology application

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dc.contributor.authorHaktanır, Elif
dc.contributor.authorKahraman, Cengiz
dc.date.accessioned2022-06-10T08:04:55Z
dc.date.available2022-06-10T08:04:55Z
dc.date.issued2022en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractPicture fuzzy sets (PFSs) are one of the most promising extensions of ordinary fuzzy sets with three parameters, namely positive membership, neutral membership, and negative membership, for defining the membership status of an element to a set. CRiteria Importance Through Intercriteria Correlation (CRITIC) & REGIME methods are recently developed multi criteria decision making (MCDM) methods for calculating the criteria weights and ranking alternatives, respectively. CRITIC method determines the criteria weights by using the values in the decision matrix. REGIME method is a compensatory MCDM method employing superiority and guide indices, superiority identifier and impacts, and REGIME matrices. In this paper, an integrated CRITIC & REGIME methodology is developed for the first time by using single-valued PFSs in order to use the advantage of PFSs in handling ambiguity and impreciseness. The main contribution of our study is to demonstrate theoretically and practically how to transform superiority and guide indices, superiority identifier and impacts, and REGIME matrices to the PF environment. A new interval valued Relative Magnitude Index scale and an original Percentile Rank under Vagueness function have been developed. The developed methodology is applied to the selection problem of wearable health technology (WHT). Comparative and sensitivity analyses are presented. These analyses show that CRITIC & REGIME methodology produces very effective and valid results, and unlike the other methods, it shows slight ranking differences due to the statistical-based calculations it contains.en_US
dc.identifier.citationHaktanır, E., & Kahraman, C. (2022). A novel picture fuzzy CRITIC & REGIME methodology: Wearable health technology application. Engineering Applications of Artificial Intelligence, 113, 104942.en_US
dc.identifier.issn0952-1976
dc.identifier.issue113en_US
dc.identifier.scopus2-s2.0-85130914201
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://hdl.handle.net/20.500.12939/2474
dc.identifier.wosWOS:000830168800011
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorHaktanır, Elif
dc.language.isoen
dc.relation.ispartofEngineering Applications of Artificial Intelligence
dc.relation.isversionof10.1016/j.engappai.2022.104942en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCOVID-19en_US
dc.subjectCriteria Importance Through Intercriteria Correlation (CRITIC)en_US
dc.subjectMulti Criteria Decision Making (MCDM)en_US
dc.subjectPicture Fuzzy Sets (PFSS)en_US
dc.subjectREGIMEen_US
dc.subjectWearable Health Technology (WHT)en_US
dc.titleA novel picture fuzzy CRITIC & REGIME methodology: Wearable health technology application
dc.typeArticle

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