scholarly journals An Evidence Combination Rule Based on Transferable Belief Model and Application in Reliability Assessment With Multi-Source Data

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 69096-69104
Author(s):  
Yuexiang Yang ◽  
Xing Pan ◽  
Qingde Cui
Keyword(s):  
Reliability Assessment ◽  
Combination Rule ◽  
Rule Based ◽  
Source Data ◽  
Evidence Combination ◽  
Belief Model ◽  
Transferable Belief Model

scholarly journals A novel weighted evidence combination rule based on improved entropy function with a diagnosis application

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771882399 ◽  
Author(s):  
Lei Chen ◽  
Ling Diao ◽  
Jun Sang
Keyword(s):  
Medical Diagnosis ◽  
Real Life ◽  
Entropy Function ◽  
New Method ◽  
Combination Rule ◽  
Initial Weight ◽  
Rule Based ◽  
Dempster Shafer Theory ◽  
Evidence Combination ◽  
Shafer Theory

Managing conflict in Dempster–Shafer theory is a popular topic. In this article, we propose a novel weighted evidence combination rule based on improved entropy function. This newly proposed approach can be mainly divided into two steps. First, the initial weight will be determined on the basis of the distance of evidence. Then, this initial weight will be modified using improved entropy function. This new method converges faster when handling high conflicting evidences and greatly reduces uncertainty of decisions, which can be demonstrated by a numerical example where the belief degree is raised up to 0.9939 when five evidences are in conflict, an application in faulty diagnosis where belief degree is increased hugely from 0.8899 to 0.9416 when compared with our previous works, and a real-life medical diagnosis application where the uncertainty of decision is reduced to nearly 0 and the belief degree is raised up to 0.9989.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Lei Chen ◽  
Ling Diao ◽  
Jun Sang
Keyword(s):  
Fault Diagnosis ◽  
Conflict Management ◽  
Information Fusion ◽  
Uncertainty Measure ◽  
Combination Rule ◽  
Rule Based ◽  
Dempster Shafer Theory ◽  
Evidence Combination ◽  
Weight Value ◽  
Shafer Theory

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.

scholarly journals The Transferable Belief Model for Failure Prediction in Wireless Sensor Networks

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Hugues Marie Kamdjou ◽  
Elie Tagne Fute ◽  
Adnen El Amraoui ◽  
Armand Nzeukou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Failure Prediction ◽  
Wireless Sensor ◽  
Belief Model ◽  
Transferable Belief Model

scholarly journals Shapley and Banzhaf Values as Probability Transformations

2018 ◽  
Vol 26 (06) ◽  
pp. 917-947 ◽  
Author(s):  
Enrique Miranda ◽  
Ignacio Montes
Keyword(s):  
Lower Probability ◽  
The Core ◽  
Belief Model ◽  
Transferable Belief Model

We investigate the role of some game solutions, such the Shapley and the Banzhaf values, as probability transformations. The first one coincides with the pignistic transformation proposed in the Transferable Belief Model; the second one is not efficient in general, leading us to consider its normalized version. We study a number of particular models of lower probabilities: minitive measures, coherent lower probabilities, as well as the lower probabilities induced by comparative or distortion models. For them, we provide some alternative expressions of the Shapley and Banzhaf values and study under which conditions they belong to the core of the lower probability.

Sign in / Sign up

Export Citation Format

Share Document