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dc.contributor.authorAtalik G.
dc.contributor.authorŞentürk S.
dc.contributor.authorKahraman C.
dc.date.accessioned2024-03-12T19:38:18Z
dc.date.available2024-03-12T19:38:18Z
dc.date.issued2023
dc.identifier.issn15423980
dc.identifier.urihttps://hdl.handle.net/20.500.12450/3035
dc.description.abstractIntuitionistic fuzzy sets theory, one of the theories used to model uncertainty, is quite successful in modeling real life uncertainties. Hypothesis testing is one of the essential tools in statistics. The methods that are combination of intuitionistic fuzzy set and statistics theory give remarkably good results in cases where the assumptions of classical methods can not be provided. In this study, the theoretical structure of intuitionistic fuzzy hypothesis testing where both data and hypothesis are triangular intuitionistic fuzzy numbers are defined for some population parameters. Also, a new ranking method based on intuitionistic fuzzy number is used to give decision in statistical hypothesis. The applicability of the intuitionistic fuzzy hypothesis testing is demonstrated on several data sets. According to results, an alternative method is presented to the researchers who want to prevent loss of information without converting fuzzy numbers to crisp numbers. © 2023 Old City Publishing, Inc.en_US
dc.language.isoengen_US
dc.publisherOld City Publishingen_US
dc.relation.ispartofJournal of Multiple-Valued Logic and Soft Computingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectbootstrap samplingen_US
dc.subjectintuitionistic fuzzy hypothesis testingen_US
dc.subjectintuitionistic fuzzy ranking methodsen_US
dc.subjectIntuitionistic fuzzy seten_US
dc.subjectpopulation mean and varianceen_US
dc.subjectFuzzy rulesen_US
dc.subjectUncertainty analysisen_US
dc.subjectBootstrap samplingsen_US
dc.subjectFuzzy hypothesisen_US
dc.subjectFuzzy ranking methoden_US
dc.subjectHypothesis testingen_US
dc.subjectIntuitionistic fuzzyen_US
dc.subjectIntuitionistic fuzzy hypothesis testingen_US
dc.subjectIntuitionistic fuzzy ranking methoden_US
dc.subjectIntuitionistic fuzzy setsen_US
dc.subjectPopulation mean and varianceen_US
dc.subjectPopulation statisticsen_US
dc.titleIntuitionistic Fuzzy Hypothesis Testing Based on a Novel Fuzzy Ranking Methoden_US
dc.typearticleen_US
dc.departmentAmasya Üniversitesien_US
dc.identifier.volume40en_US
dc.identifier.issue3-4en_US
dc.identifier.startpage285en_US
dc.identifier.endpage304en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-85169541578en_US
dc.department-tempAtalik, G., Department of Architecture, Amasya University, Turkey; Şentürk, S., Department of Statistics, Eskisehir Technical University, Turkey; Kahraman, C., Department of Industrial Engineering, Istanbul Technical University, Turkeyen_US
dc.authorscopusid57200637439
dc.authorscopusid25631133000
dc.authorscopusid7003388495


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