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An association coefficient of a belief function and its application in a target recognition system
Author(s) -
Pan Lipeng,
Deng Yong
Publication year - 2020
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.22200
Subject(s) - association (psychology) , similarity (geometry) , function (biology) , entropy (arrow of time) , association rule learning , mathematics , gini coefficient , computer science , statistics , artificial intelligence , inequality , epistemology , image (mathematics) , mathematical analysis , physics , philosophy , thermodynamics , evolutionary biology , biology , economic inequality
The conflict problem in D‐S evidence theory has attracted the attention of many scholars. Conflict coefficients are proposed to describe conflicts between bodies of evidence. The association coefficient as the opposite of the conflict coefficient is also used to measure the conflict. The larger the association coefficient, the smaller the conflict degree, and the higher the similarity between the evidence bodies, and vice versa. In this paper, the degree of association is defined by Deng Entropy, and a new association coefficient is proposed based on the basic inequality. The nature of the new association coefficient and conflict coefficients is explored using examples. Finally, the association coefficient combined with the D‐S combination rule is applied to the target recognition system, and accurate results are obtained.