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Basic probability assignment to probability distribution function based on the Shapley value approach

delete2021-05-18
delete22
PRE
AI
C
Chongru Huang
X
Xiangjun Mi
康兵义 (Bingyi Kang) *
DOI:10.1002/int.22456delete
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Abstract

Abstract

En 中文
In Dempster-Shafer evidence theory, how to use the basic probability assignment (BPA) in decision-making is a significant issue. The transformation of BPA into a probability distribution function is one of the common and feasible schemes. To overcome the problems of the existing methods, we propose a marginal probability transformation method based on the Shapley value approach. The proposed method allocates BPA values in terms of how much an element contributes to a set, which is an equitable and effective distribution mechanism. Furthermore, we use probabilistic information content to evaluate the effect of each transformation method. Moreover, some numerical examples are used to demonstrate the efficiency and feasibility of the proposed method. Further, two applications, target recognition, fault diagnosis are used to verify the superiority and effectiveness of the proposed method in practice.
Keywords:
Dempster– Shafer evidence theory
fault diagnosis
marginal probability
probabilistic information content
probability transformation
Shapley value
target recognition

Journal

International Journal of Intelligent Systems cover
International Journal of Intelligent Systems
IF:
3.7
Papers:
3.0K
Citations:
8.1K

Organization

N
northwest a&f university - china
Scholars:
3.6W
Papers: 2.1W
Citations: 34