Weighted Evidence Combination Based on Distance of Evidence and Entropy Function Article Swipe

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Computer science Entropy (arrow of time) Information fusion Weight function Convergence (economics) Algorithm Data mining Mathematical optimization Artificial intelligence Mathematics Statistics Quantum mechanics Economic growth Economics Physics

Jianwei Wang , Fuyuan Xiao , Xinyang Deng , Liguo Fei , Yong Deng ·

YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.1177/155014773218784 · OA: W2491356680

Conflict management in Dempster-Shafer theory (D-S theory) is a hot topic in information fusion. In this paper, a new weighted evidence combination on the basis of the distance between evidence and entropy function is presented. The proposed approach is identified as two procedures. First, the weight is determined based on the distance of evidence. Then, the obtained weight value in the first step is modified by making advantage of Deng entropy function. Our proposed method can efficiently cope with high conflicting evidences with better performance of convergence. A numerical example is provided to demonstrate that the proposed method is reasonable and efficient in the end.