On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory

Journal of Intelligent Systems 32 (1) (2023)
  Copy   BIBTEX

Abstract

Knowledge reduction of information systems is one of the most important parts of rough set theory in real-world applications. Based on the connections between the rough set theory and the theory of topology, a kind of topological reduction of incomplete information systems is discussed. In this study, the topological reduction of incomplete information systems is characterized by belief and plausibility functions from evidence theory. First, we present that a topological space induced by a pair of approximation operators in an incomplete information system is pseudo-discrete, which deduces a partition. Then, the topological reduction is characterized by the belief and plausibility function values of the sets in the partition. A topological reduction algorithm for computing the topological reducts in incomplete information systems is also proposed based on evidence theory, and its efficiency is examined by an example. Moreover, relationships among the concepts of topological reduct, classical reduct, belief reduct, and plausibility reduct of an incomplete information system are presented.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 100,865

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

The Relation Between Rough Sets And Fuzzy Sets Via Topological Spaces.M. E. Ali & T. Medhat - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (10):1-10.
Dynamic Topological Logic Interpreted over Minimal Systems.David Fernández-Duque - 2011 - Journal of Philosophical Logic 40 (6):767-804.
Rough Neutrosophic Sets.Said Broumi, Florentin Smarandache & Mamoni Dhar - 2014 - Neutrosophic Sets and Systems 3:60-65.

Analytics

Added to PP
2023-01-13

Downloads
14 (#1,273,358)

6 months
2 (#1,686,184)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references