Weighted Evidence Combination Rule Based on Evidence Distance and Uncertainty Measure: An Application in Fault Diagnosis

Conflict management in Dempster-Shafer theory (D-S theory) is a hot topic in information fusion. In this paper, a novel weighted evidence combination rule based on evidence distance and uncertainty measure is proposed. The proposed approach consists of two steps. First, the weight is determined base...

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Bibliographic Details
Published in:Mathematical problems in engineering 2018-01, Vol.2018 (2018), p.1-10
Main Authors: Chen, Lei, Sang, Jun, Diao, Ling
Format: Article
Language:English
Subjects:
Artificial intelligence
Data integration
Decision making
Engineering
Fault diagnosis
Fuzzy logic
Mathematical problems
Multisensor fusion
Neural networks
Sensors
Target recognition
Uncertainty
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Summary:Conflict management in Dempster-Shafer theory (D-S theory) is a hot topic in information fusion. In this paper, a novel weighted evidence combination rule based on evidence distance and uncertainty measure is proposed. The proposed approach consists of two steps. First, the weight is determined based on the evidence distance. Then, the weight value obtained in first step is modified by taking advantage of uncertainty. Our proposed method can efficiently handle high conflicting evidences with better performance of convergence. A numerical example and an application based on sensor fusion in fault diagnosis are given to demonstrate the efficiency of our proposed method.
ISSN:1024-123X
1563-5147
DOI:10.1155/2018/5858272