Probability estimation in the framework of intuitionistic fuzzy evidence theory
type: Item
instance of: scholarly article
title: Probability estimation in the framework of intuitionistic fuzzy evidence theory
zbMATH Open document ID: 1394.68389
DOI: 10.1155/2015/412045
author: Yafei Song
author: Xiaodan Wang
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: Intuitionistic fuzzy (IF) evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.
Mathematics Subject Classification ID: 68T37
Mathematics Subject Classification ID: 62G05
zbMATH DE Number: 6926294
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/412045
OpenAlex ID: W1977407373
Wikidata QID: Q59118510
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description: scientific article; zbMATH DE number 6926294