Small Infrared Targets Recognition with New Evidence Combination Approach

2011 ◽  
Author(s):  
Chen Liangzhou ◽  
Qu Dan ◽  
Du Feng
Keyword(s):  
Evidence Combination ◽  
Combination Approach ◽  
New Evidence

Evidence combination approach based on uncertainty measure

2009 ◽  
Vol 29 (8) ◽  
pp. 2257-2259 ◽  
Author(s):  
Wen-jun XIA ◽  
Lin-hu ZHU ◽  
Tao-rong LU
Keyword(s):  
Uncertainty Measure ◽  
Evidence Combination ◽  
Combination Approach

An improved conflicting evidence combination approach based on a new supporting probability distance

2015 ◽  
Vol 42 (12) ◽  
pp. 5139-5149 ◽  
Author(s):  
Cholsok Yu ◽  
Jianhong Yang ◽  
Debin Yang ◽  
Xianghong Ma ◽  
Hyonchun Min
Keyword(s):  
Conflicting Evidence ◽  
Evidence Combination ◽  
Combination Approach ◽  
Probability Distance

A Novel Batch-Mode Evidence Combination Approach

2011 ◽  
Vol 9 (5) ◽  
pp. 2073-2077 ◽  
Author(s):  
Deqiang Han ◽  
Yong Deng ◽  
Chongzhao Han ◽  
Yi Yang
Keyword(s):  
Batch Mode ◽  
Evidence Combination ◽  
Combination Approach

Conflicting evidence combination based on Belief Mover’s Distance

2021 ◽  
pp. 1-17
Author(s):  
Shenshen Bai ◽  
Longjie Li ◽  
Xiaoyun Chen
Keyword(s):  
Information Fusion ◽  
Evidence Theory ◽  
Weighted Average ◽  
Combination Rule ◽  
The Earth ◽  
Conflicting Evidence ◽  
Evidence Combination ◽  
Final Weight ◽  
The Difference ◽  
New Evidence

The Dempster-Shafer evidence theory has been extensively used in various applications of information fusion owing to its capability in dealing with uncertain modeling and reasoning. However, when meeting highly conflicting evidence, the classical Dempster’s combination rule may give counter-intuitive results. To address this issue, we propose a new method in this work to fuse conflicting evidence. Firstly, a new evidence distance metric, named Belief Mover’s Distance, which is inspired by the Earth Mover’s Distance, is defined to measure the difference between two pieces of evidence. Subsequently, the credibility weight and distance weight of each piece of evidence are computed according to the Belief Mover’s Distance. Then, the final weight of each piece of evidence is generated by unifying these two weights. Finally, the classical Dempster’s rule is employed to fuse the weighted average evidence. Several examples and applications are presented to analyze the performance of the proposed method. Experimental results manifest that the proposed method is remarkably effective in comparison with other methods.

scholarly journals A Weighted Evidence Combination Approach for Target Identification in Wireless Sensor Networks

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 21585-21596 ◽  
Author(s):  
Yang Zhang ◽  
Yun Liu ◽  
Zhenjiang Zhang ◽  
Han-Chieh Chao ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Identification ◽  
Wireless Sensor ◽  
Evidence Combination ◽  
Combination Approach
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