Numerical Characterizations of Topological Reductions of Covering Information Systems in Evidence Theory
Author(s) -
Yan-Lan Zhang,
Changqing Li
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/6648108
Subject(s) - rough set , mathematics , topology (electrical circuits) , topological space , reduction (mathematics) , set (abstract data type) , information theory , set theory , function (biology) , discrete mathematics , computer science , data mining , combinatorics , geometry , statistics , evolutionary biology , biology , programming language
The reductions of covering information systems in terms of covering approximation operators are one of the most important applications of covering rough set theory. Based on the connections between the theory of topology and the covering rough set theory, two kinds of topological reductions of covering information systems are discussed in this paper, which are characterized by the belief and plausibility functions from the evidence theory. The topological spaces by two pairs of covering approximation operators in covering information systems are pseudo-discrete, which deduce partitions. Then, using plausibility function values of the sets in the partitions, the definitions of significance and relative significance of coverings are presented. Hence, topological reduction algorithms based on the evidence theory are proposed in covering information systems, and an example is adopted to illustrate the validity of the algorithms.
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