Premium
Evaluation method based on fuzzy relations between Dempster–Shafer belief structure
Author(s) -
Zheng Haoyang,
Deng Yong
Publication year - 2018
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21956
Subject(s) - dempster–shafer theory , membership function , fuzzy logic , fuzzy set , transformation (genetics) , probability distribution , artificial intelligence , computer science , degree (music) , set (abstract data type) , belief structure , function (biology) , mathematics , type 2 fuzzy sets and systems , data mining , statistics , biochemistry , chemistry , physics , evolutionary biology , biology , acoustics , gene , programming language
Many relations in the real world can be described by mathematical language. Fuzzy set theory can transform human language into mathematical language and use membership degree function to describe relations between events. Dempster–Shafer evidence theory provides basic probability assignment (BPA), which can describe the occurrence rate of attributes in basic events. Based on the known membership degree function and BPA distribution, a new evaluation method is proposed in this paper to analyze decision making. Given the relations among relevant events, which are expressed by BPA distribution and membership degree function, the relations among basic events and top event can be obtained. The Dempster's combination rule and pignistic probability transformation are used to transform BPA distribution into probability distribution. The belief measure is applied to deal with these fuzzy relations. Some numerical examples are given in this paper to illustrate the proposed evaluation methodology.