Covering-Based Rough Single Valued Neutrosophic Sets

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