scholarly journals Conflict Management in Information Fusion with Belief Functions

2019 ◽  
pp. 79-97 ◽  
Author(s):  
Arnaud Martin
Keyword(s):  
Conflict Management ◽  
Information Fusion ◽  
Belief Functions

scholarly journals Integration of Extra-Information for Belief Function Theory Conflict Management Problem Through Generic Association Rules

2014 ◽  
Vol 22 (04) ◽  
pp. 531-551 ◽  
Author(s):  
Ahmed Samet ◽  
Eric Lefèvre ◽  
Sadok Ben Yahia
Keyword(s):  
Decision Making ◽  
Conflict Management ◽  
Information Fusion ◽  
Information Sources ◽  
Function Theory ◽  
Belief Function ◽  
Management Approach ◽  
Management Problem ◽  
Extra Information ◽  
Belief Function Theory

Decision making by considering multiple information sources could provide interesting results. For that reason, fusion formalisms were a major concern in the belief function community. In this context, the Belief function theory allows information fusion thanks to its combinations tools that it integrates. Nevertheless, belief function theory highlights a limit in the merging of contradictory (conflictual) sources. Many authors tackled this problem offering contributions in this field. Unfortunately, no proposed operator has distinguished by its adequacy regardless the type of handled sources. In this paper, we demonstrate the limits of some referenced works and we diagnostic the issues origin. We propose a conflict management approach based on an extra-information that guides the treatment. We also integrate a generic associative base borrowed from the data mining domain in order to apply the adequate conflict management.

scholarly journals Information Fusion With Belief Functions for Detection of Interturn Short-Circuit Faults in Electrical Machines Using External Flux Sensors

2018 ◽  
Vol 65 (3) ◽  
pp. 2642-2652 ◽  
Author(s):  
Miftah Irhoumah ◽  
Remus Pusca ◽  
Eric Lefevre ◽  
David Mercier ◽  
Raphael Romary ◽  
...  
Keyword(s):  
Information Fusion ◽  
Short Circuit ◽  
Electrical Machines ◽  
Belief Functions

scholarly journals Reply to the Comments of R. Haenni on the paper “Belief functions combination and conflict management”

2003 ◽  
Vol 4 (1) ◽  
pp. 63-65 ◽  
Author(s):  
E. Lefevre ◽  
O. Colot ◽  
P. Vannoorenberghe
Keyword(s):  
Conflict Management ◽  
Belief Functions

Milling Tool Wear Identification Using Information Fusion

2014 ◽  
Vol 496-500 ◽  
pp. 1681-1684
Author(s):  
Chuang Wen Xu
Keyword(s):  
Tool Wear ◽  
Information Fusion ◽  
Evidence Theory ◽  
Reliability Function ◽  
Belief Functions ◽  
Combination Rule ◽  
Literature Study ◽  
Wear Characteristics ◽  
Milling Tool ◽  
Information Characteristics

Milling tool wear identification literature study, some information characteristics was generated by a number of possible milling tool wear. In theory, the characteristics of each of the information under the milling tool wear has a certain probability of occurring. DS evidence theory, belief functions used to express the size of the probability. the milling tool wear objects was identified through multi-sensor testing, then, measured the information features of each sensor belong to belief functions was obtained, then use the DS combination rule for information fusion, information fusion can be milling tool wear characteristics belong to the reliability function, the final determination based on certain criteria for determining status of milling tool wear type and size of tool wear.

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 A Robust DS Combination Method Based on Evidence Correction and Conflict Redistribution

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Fang Ye ◽  
Jie Chen ◽  
Yuan Tian
Keyword(s):  
Conflict Management ◽  
Information Fusion ◽  
Evidence Theory ◽  
Combination Method ◽  
The Novel ◽  
Degree Function ◽  
The One ◽  
Reliability And Robustness ◽  
Evidence Credibility ◽  
Fusion Approach

To eliminate potential evidence conflicts, an effective and accurate DS combination method is addressed in this paper. DS evidence theory is an outstanding information fusion approach with valid uncertainty treatment. Nevertheless, there are some limitations of the usage of the DS evidence theory. On the one hand, due to the complexity of a combat measurement environment and the inconsistency of sensor capabilities, sensor sources have enormous uncertainty, which would inevitably cause conflicts for evidence combination. On the other hand, DS combination rule realizes the unity property of fusing results with a compulsive normalization, which unavoidably leads to conflicting situations. To solve the possible evidence conflicts in a multisensor fusion system, we raise a robust DS combination method based on evidence correction and conflict redistribution. Firstly, two corrected indexes—the reliability index and consistency index—are separately addressed with the introduction of the Matusita distance function and closeness degree function. After the evidence modification based on two correction indexes, the conflicts caused by unreliable sensor sources are solved. Then, based on the corrected evidences, we put forward a weighted assignment of conflicting mass where the weight index lies on the evidence credibility. As the normalization step is abolished, the conflict redistribution strategy avoids the conflicts caused by straightforward normalization. Through comprehensive conflict management, the proposed DS combination method can not only guarantee the rationality and availability of fusing results, but also enhance the reliability and robustness of a multisensor system. Finally, three combination experiments with different conflicting degrees illustrate the advantage and superiority of the novel combination method for conflict management. Consequently, the innovation of the novel algorithm is verified.

Sign in / Sign up

Export Citation Format

Share Document