Conflicting evidence combination based on uncertainty measure and distance of evidence

Wen Jiang, Miaoyan Zhuang, Xiyun Qin, Yongchuan Tang

科研成果: 期刊稿件文章同行评审

32 引用 (Scopus)

摘要

Dempster–Shafer evidence theory is widely used in many fields of information fusion. However, the counter-intuitive results may be obtained when combining with highly conflicting evidence. To deal with such a problem, we put forward a new method based on the distance of evidence and the uncertainty measure. First, based on the distance of evidence, the evidence is divided into two parts, the credible evidence and the incredible evidence. Then, a novel belief entropy is applied to measure the information volume of the evidence. Finally, the weight of each evidence is obtained and used to modify the evidence before using the Dempster’s combination rule. Numerical examples show that the proposed method can effectively handle conflicting evidence with better convergence.

源语言英语
文章编号1217
期刊SpringerPlus
5
1
DOI
出版状态已出版 - 1 12月 2016

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