Rough set theory introduced by Pawlak [8] is based on equivalence relations. The definition of basic rough sets depends upon a single equivalence relation defined on the universe or several equivalence relations taken one each taken at a time. In the view of granular computing, classical rough set theory is based upon single granulation. The basic rough set model was extended to rough set model...

Both neutrosophic sets theory and rough sets theory are emerging as powerful tool for managing uncertainty, indeterminate, incomplete and imprecise information .In this paper we develop an hybrid structure called “ rough neutrosophic sets” and studied their properties.

Rough set theory has become well-established as a mechanism for uncertainty management in a wide variety of applications including databases. This paper addresses the measurement of uncertainty in rough sets and rough relational databases by introducing a measurement based on information theory. This rough entropy is discussed as it applies to rough sets in general, and in particular to aspects...

Rough set theory provides a useful mathematical concept to draw tends to serve well for data mining applications whereas the predictive model. The rough set toolkit for analysis of data (ROSETTA), which is an advanced machine learning algorithms for data mining tasks implemented in Java (33). Therefore, this paper presents the RoughSets package that allows researchers. Zdzislaw Pawlak, Rough Se...

Soft set theory is a newly emerging tool to deal with uncertain problems. Based on soft sets, soft rough approximation operators are introduced, and soft rough sets are defined by using soft rough approximation operators. Soft rough sets, which could provide a better approximation than rough sets do, can be seen as a generalized rough set model. This paper is devoted to investigating soft rough...

The notion of a rough set was originally proposed by Pawlak [Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences 11 (5) (1982) 341–356]. Later on, Dubois and Prade [D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, International Journal of General System 17 (2–3) (1990) 191–209] introduced rough fuzzy sets and fuzzy rough sets as a generalization of rough...

At present, practical application and theoretical discussion of rough sets are two hot problems in computer science. The core concepts of rough set theory are upper and lower approximation operators based on equivalence relations. Matroid, as a branch of mathematics, is a structure that generalizes linear independence in vector spaces. Further, matroid theory borrows extensively from the termin...

Rough set theory, a mathematical tool to deal with vague concepts, has originally described the indiscernibility of elements by equivalence relations. Covering-based rough sets are a natural extension of classical rough sets by relaxing the partitions arising from equivalence relations to coverings. Recently, some topological concepts such as subbase, neighborhood and separation axioms have bee...

Medical science is not an exact science in which processes can be easily analyzed and modeled. Rough set theory has proven well suited for accommodating such inexactness of the medical profession. As rough set theory matures and its theoretical perspective is extended, the theory has been also followed by development of innovative rough sets systems as a result of this maturation. Unique concer...