Evidence combination approach based on uncertainty measure

Abstract

Focusing on the problem that the Dempster's combination rule cannot effectively combine conflict evidences and the high computational complexity of the present solution method based on distance between evidences, a weighted average evidence combination approach was proposed. First, the computational complexity of combination rule proposed by Deng Yong, taken as an instance of combination rules based on distance between evidences, was calculated and analyzed. Then the concept of uncertainty measure of evidence was used to describe the uncertainty of evidence body and as a basis of determining the weight of evidence. The numerical example shows that the evidence combination approach based on uncertainty measure can efficiently combine evidences, whether they conflict with each other or not, with faster convergence speed as well as lower computational complexity compared with those based on the distance between the evidences.