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Connections between rough set theory and Dempster-Shafer theory of evidence

International Journal of General SystemsPublished 1 July 2002
Wei-Zhi Wu, Yee Leung, Wen‐Xiu Zhang
Citations123
SJR quartileQ2
SJR score0.56
SNIP1.17

TL;DR

It is demonstrated that various belief structures are associated with various rough approximation spaces such that different dual pairs of upper and lower approximation operators induced by therough approximation spaces may be used to interpret the corresponding dual pairsof plausibility and belief functions induced byThe Dempster-Shafer theory of evidence.

Abstract

In rough set theory there exists a pair of approximation operators, the upper and lower approximations, whereas in Dempster-Shafer theory of evidence there exists a dual pair of uncertainty measures, the plausibility and belief functions. It seems that there is some kind of natural connection between the two theories. The purpose of this paper is to establish the relationship between rough set theory and Dempster-Shafer theory of evidence. Various generalizations of the Dempster-Shafer belief structure and their induced uncertainty measures, the plausibility and belief functions, are first reviewed and examined. Generalizations of Pawlak approximation space and their induced approximation operators, the upper and lower approximations, are then summarized. Concepts of random rough sets, which include the mechanisms of numeric and non-numeric aspects of uncertain knowledge, are then proposed. Notions of the Dempster-Shafer theory of evidence within the framework of rough set theory are subsequently formed and interpreted. It is demonstrated that various belief structures are associated with various rough approximation spaces such that different dual pairs of upper and lower approximation operators induced by the rough approximation spaces may be used to interpret the corresponding dual pairs of plausibility and belief functions induced by the belief structures.

Keywords

Computer ScienceDecision Sciences