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• W4281651386 abstract "We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random fuzzy sets are combined by the generalized product-intersection rule, which extends both Dempster's rule for combining belief functions, and the product conjunctive combination of possibility distributions. We introduce Gaussian random fuzzy numbers and their multi-dimensional extensions, Gaussian random fuzzy vectors, as practical models for quantifying uncertainty about scalar or vector quantities. Closed-form expressions for the combination, projection and vacuous extension of Gaussian random fuzzy numbers and vectors are derived." @default.
• W4281651386 created "2022-06-13" @default.
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• W4281651386 date "2023-02-01" @default.
• W4281651386 modified "2023-10-16" @default.
• W4281651386 title "Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: General framework and practical models" @default.
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• W4281651386 doi "https://doi.org/10.1016/j.fss.2022.06.004" @default.
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