Add to ORKGIn this paper we study the rough probability in the topological spaces which we can consider them as results from the general relations on the approximation spaces
This paper can be viewed as a generalization of Pawlak approximation space using general topological...
A rough set is a formal approximation of a crisp set which gives lower and upper approximation of or...
Abstract—Rough set theory has proven to be an efficient tool for modeling and reasoning with uncerta...
In this paper we study the rough probability in the topological spaces which we can consider them as...
The main aim of the rough set is reducing the boundary region by increasing the lower approximation ...
In 1982, the theory of rough sets proposed by Pawlak and in 2013, Luay concerned a rough probability...
Rough approximation operators in approximation spaces are the core concept of rough set theory, whic...
Abstract. In the paper we discuss approximation spaces relevant for rough-neuro computing
AbstractThe original rough set model was developed by Pawlak, which is mainly concerned with the app...
Rough sets, developed by Pawlak, are an important model of incomplete or partially known information...
The concept of topological group is a simple combination of the concepts of abstract group and topol...
AbstractRough approximation operators in approximation spaces are the core concept of rough set theo...
We establish some deterministic and random approximation results with the help of two continuous map...
Abstract — In this paper we propose that a vague set can be approximated by two vague sets in Pawlak...
AbstractIn this paper a generalized notion of an approximation space is considered. By an approximat...
This paper can be viewed as a generalization of Pawlak approximation space using general topological...
A rough set is a formal approximation of a crisp set which gives lower and upper approximation of or...
Abstract—Rough set theory has proven to be an efficient tool for modeling and reasoning with uncerta...
In this paper we study the rough probability in the topological spaces which we can consider them as...
The main aim of the rough set is reducing the boundary region by increasing the lower approximation ...
In 1982, the theory of rough sets proposed by Pawlak and in 2013, Luay concerned a rough probability...
Rough approximation operators in approximation spaces are the core concept of rough set theory, whic...
Abstract. In the paper we discuss approximation spaces relevant for rough-neuro computing
AbstractThe original rough set model was developed by Pawlak, which is mainly concerned with the app...
Rough sets, developed by Pawlak, are an important model of incomplete or partially known information...
The concept of topological group is a simple combination of the concepts of abstract group and topol...
AbstractRough approximation operators in approximation spaces are the core concept of rough set theo...
We establish some deterministic and random approximation results with the help of two continuous map...
Abstract — In this paper we propose that a vague set can be approximated by two vague sets in Pawlak...
AbstractIn this paper a generalized notion of an approximation space is considered. By an approximat...
This paper can be viewed as a generalization of Pawlak approximation space using general topological...
A rough set is a formal approximation of a crisp set which gives lower and upper approximation of or...
Abstract—Rough set theory has proven to be an efficient tool for modeling and reasoning with uncerta...