Information Granule Based Uncertainty Measure of Fuzzy Evidential Distribution

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dc.authoridZhou, Qianli/0000-0001-5087-3617
dc.authorwosidZhou, Qianli/KEI-1380-2024
dc.contributor.authorZhou, Qianli
dc.contributor.authorPedrycz, Witold
dc.contributor.authorLiang, Yingying
dc.contributor.authorDeng, Yong
dc.date.accessioned2024-05-19T14:41:22Z
dc.date.available2024-05-19T14:41:22Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractQuantifying the uncertainty of information distributions containing randomness, imprecision, and fuzziness is the premise of processing them. A useful information representation in the field of intelligent computing are information granules, which optimize data from the perspective of specificity and coverage. We introduce information granularity into evidential information and model the basic probability assignment (BPA) as a weighted information granules model. Based on the proposed model, a new uncertainty measure of BPA is derived from the quality evaluation of granules. In addition, the proposed measure is extended to fuzzy evidential information distributions. When the Fuzzy BPA (FBPA) degenerates into the Probability Mass Function (ProbMF) and Possibility Mass Function (PossMF), the proposed method degenerates to Gini entropy and Yager's specificity measure, respectively. We use a refined belief structure to interpret the meaning of FBPA in the transfer belief model, and verify the validity of the proposed method by analyzing its properties and presenting numerical examples. The concept of information granule is used for the first time to model focal set and beliefs. Compared with Shannon entropy based information measures, the proposed method provides a novel perspective on the relationship between randomness, imprecision, and fuzziness in FBPA.en_US
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_US
dc.description.sponsorshipNo Statement Availableen_US
dc.identifier.doi10.1109/TFUZZ.2023.3284713
dc.identifier.endpage4396en_US
dc.identifier.issn1063-6706
dc.identifier.issn1941-0034
dc.identifier.issue12en_US
dc.identifier.scopus2-s2.0-85162670133en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage4385en_US
dc.identifier.urihttps://doi.org10.1109/TFUZZ.2023.3284713
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5100
dc.identifier.volume31en_US
dc.identifier.wosWOS:001123573900021en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Fuzzy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectEvennessen_US
dc.subjectFuzzy Dempster-Shafer Theoryen_US
dc.subjectInformation Granule (Ig)en_US
dc.subjectQuality Evaluationen_US
dc.subjectSpecificity And Coverageen_US
dc.subjectUncertaintyen_US
dc.titleInformation Granule Based Uncertainty Measure of Fuzzy Evidential Distributionen_US
dc.typeArticleen_US

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