title: Conflicting evidence combination based on uncertainty measure and distance of evidence.
abstract: 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.
authors: School of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072 Shaanxi China.
authors: Wen
authors: 0000-0001-5429-2748
authors: W
authors: Jiang
authors: School of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072 Shaanxi China.
authors: Miaoyan
authors: M
authors: Zhuang
authors: School of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072 Shaanxi China.
authors: Xiyun
authors: X
authors: Qin
authors: School of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072 Shaanxi China.
authors: Yongchuan
authors: Y
authors: Tang
keywords: Belief entropy; Conflict; Dempster–Shafer evidence theory; Distance of evidence; Information fusion