Numerical Characterizations of Topological Reductions of Covering Information Systems in Evidence Theory

Abstract

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.

Innovation of Visual Communication Design of Interactive Packaging for Internet-Famous Food Based on Artificial Intelligence

“…As an uncertain reasoning method, evidence theory has unique advantages in information fusion and has been widely used [26][27][28][29][30][31][32][33][34]. When the evaluation information of the multiple groups supports the proposition that "the innovation of interactive packaging design is the best," when these evidences are fused together, the fusion results should support this proposition to a greater extent.…”