A generalized evidence distance  

作　　者：Hongming Mo Xi Lu Yong Deng 

机构地区：[1]School of Computer and Information Science, Southwest University, Chongqing 400715, China [2]Department of the Tibetan Language, Sichuan University for Nationalities, Kangding 626001, China [3]School of Hanhong, Southwest University, Chongqing 400715, China

出　　处：《Journal of Systems Engineering and Electronics》2016年第2期470-476,共7页系统工程与电子技术（英文版）

基　　金：supported by the National High Technology Research and Development Program of China(863 Program)(2013AA013801);the National Natural Science Foundation of China(61174022;61573290);the open funding project of State Key Laboratory of Virtual Reality Technology and Systems;the Beihang University(BUAA-VR-14KF-02);the General Research Program of Natural Science of Sichuan Provincial Department of Education(14ZB0322);the Self-financing Program of State Ethnic Affairs Commission of China(14SCZ014)

摘　　要：How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.

关 键 词：Dempster-Shafer evidence（D-S） theory basic probability assignment（BPA） belief function evidence distance similarity function 

分 类 号：O211[理学—概率论与数理统计]