Covering-Based Rough Single Valued Neutrosophic Sets

Abstract

Rough sets theory is a powerful tool to deal with uncertainty and incompleteness of knowledge in information systems.
Wang et al. proposed single valued neutrosophic sets as an extension
of intuitionistic fuzzy sets to deal with real-world problems. In this
paper, we propose the covering-based rough single valued neutrosophic sets by combining covering-based rough sets and single valued neutrosophic sets. Firstly, three types of covering-based rough
single valued neutrosophic sets models are built and the properties
of lower/upper approximation operators are explored. Secondly, the
lower/upper approximations in two different covering approximation
spaces are studied. The sufficient and necessary condition for generating the same lower/upper approximations from two different covering approximation spaces is discussed. Moreover, the relations of the
three models are discussed and the equivalence conditions for three
models are given.