Weighted Conflict Evidence Combination Method Based on Hellinger Distance and the Belief Entropy
Junwei Li, Baolin Xie, Yong Jin, Zhentao Hu, Lin Zhou
Abstract
In the Dempster-Shafer evidence theory, how to effectively measure the degree of conflict between two bodies of evidence is still an open question. To solve this problem, we propose a weighted conflict evidence combination method based on Hellinger distance and the belief entropy. This method uses the probability transformation function to deal with the multi-subset focal elements firstly. Next, the Hellinger distance is introduced to measure the degree of conflict among the evidence. Moreover, improved belief entropy is also employed to quantify the uncertainty of the basic belief assignments. Further, Hellinger distance and the improved belief entropy are combined to construct the weight coefficient concerning evidence, and finally, the Dempster combination rule is used for fusion. The final fusion results of proposed method on fault diagnosis experiment and target recognition experiment are 0.9018 and 0.9895 respectively, apparently higher than that of other methods, revealing the advantages of the proposed method.