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Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence

Authors :
Thierry Denœux
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc)
Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS)
Institut Universitaire de France (IUF)
Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.)
Source :
Fuzzy Sets and Systems, Fuzzy Sets and Systems, Elsevier, 2021, 424, pp.63-91. ⟨10.1016/j.fss.2020.12.004⟩
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

International audience; We revisit Zadeh's notion of "evidence of the second kind" and show that it provides the foundation for a general theory of epistemic random fuzzy sets, which generalizes both the Dempster-Shafer theory of belief functions and possibility theory. In this perspective, Dempster-Shafer theory deals with belief functions generated by random sets, while possibility theory deals with belief functions induced by fuzzy sets. The more general theory allows us to represent and combine evidence that is both uncertain and fuzzy. We demonstrate the application of this formalism to statistical inference, and show that it makes it possible to reconcile the possibilistic interpretation of likelihood with Bayesian inference.

Details

Language :
English
ISSN :
01650114
Database :
OpenAIRE
Journal :
Fuzzy Sets and Systems, Fuzzy Sets and Systems, Elsevier, 2021, 424, pp.63-91. ⟨10.1016/j.fss.2020.12.004⟩
Accession number :
edsair.doi.dedup.....e502d5920200039408bce11c90a24505
Full Text :
https://doi.org/10.1016/j.fss.2020.12.004⟩