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

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 cover...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mathematical problems in engineering Jg. 2021; S. 1 - 9
Hauptverfasser: Zhang, Yan-Lan, Li, Chang-Qing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi 31.03.2021
John Wiley & Sons, Inc
Schlagworte:
Algorithms
Approximation
Engineering
Information systems
Mathematical analysis
Mathematical functions
Operators (mathematics)
Partitions
Set theory
Topology
Universe
ISSN:1024-123X, 1563-5147
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/6648108