Open AccessA Novel Evidence Distance in Power Set Space
Author(s) -
Lei Zheng,
Jiawei Zou,
Baoyu Liu,
Yong Hu,
Yong Deng
Publication year - 2019
Publication title -
the international arab journal of information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 27
eISSN - 2309-4524
pISSN - 1683-3198
DOI - 10.34028/iajit/17/1/2
Subject(s) - measure (data warehouse) , computer science , triangle inequality , similarity measure , compatibility (geochemistry) , distance measures , set (abstract data type) , similarity (geometry) , mathematical optimization , topology (electrical circuits) , algorithm , mathematics , discrete mathematics , data mining , artificial intelligence , combinatorics , geochemistry , image (mathematics) , programming language , geology
Distance measure of evidence presented has been used to measure the similarity of two bodies of evidence. However, it is not considered that the probability distribution on a power set is able to assign to its subsets not only single elements. In this paper a novel approach is proposed to measure the distance of evidence. And some properties that the novel approach has, such as nonnegativity, symmetry, triangular inequality, downward compatibility and higher sensitivity, is proved. Numerical example and real application are used to strictly illustrate the efficiency of the new distance.
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