This paper extends the study of multi-fuzzy rough sets using an implicator and a continuous t-norm and thus introduces multi-fuzzy rough sets based on fuzzy logical connectives. In this constructive approach, a pair of lower and upper approximation operators determined by an implicator and a triangular norm is defined. The fundamental properties of these approximation operators are examined. Connections between multi-fuzzy relations and the newly constructed multi-fuzzy rough approximation operators are also established. The theory of multi-fuzzy rough sets is analysed using an operator oriented view in the later sections. The lower and upper approximation operators are characterized by axioms. Various axiom sets of lower and upper multi-fu...
In fuzzy rough sets a fuzzy T-similarity relation is employed to describe the degree of similarity b...
AbstractThe primitive notions in rough set theory are lower and upper approximation operators define...
The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulatio...
In this paper, we present an extension of the well-known implicator/t-norm based fuzzy rough set mod...
In this paper, we present an extension of the well-known implicator/t-norm based fuzzy rough set mod...
This paper presents a general frameworkfor the study of rough set approximation operators in fuzzy e...
Ever since the first hybrid fuzzy rough set model was pro- posed in the early 1990¿s, many researche...
Abstract. Ever since the first hybrid fuzzy rough set model was pro-posed in the early 1990’s, many ...
Abstract In this paper, a general framework for the study of dual fuzzy rough approximation operator...
This work was partially supported by the Spanish Ministry of Science and Technology under Project TI...
AbstractWe propose a new fuzzy rough set approach which, differently from most known fuzzy set exten...
Approximation operators play a vital role in rough set theory. Their three elements, namely, binary ...
Approximation operators play a vital role in rough set theory. Their three elements, namely, binary ...
AbstractThis paper focuses on the generalization of covering-based rough set models via the concept ...
The starting point of the paper is the (well-known) observation that the classical Rough Set Theory ...
In fuzzy rough sets a fuzzy T-similarity relation is employed to describe the degree of similarity b...
AbstractThe primitive notions in rough set theory are lower and upper approximation operators define...
The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulatio...
In this paper, we present an extension of the well-known implicator/t-norm based fuzzy rough set mod...
In this paper, we present an extension of the well-known implicator/t-norm based fuzzy rough set mod...
This paper presents a general frameworkfor the study of rough set approximation operators in fuzzy e...
Ever since the first hybrid fuzzy rough set model was pro- posed in the early 1990¿s, many researche...
Abstract. Ever since the first hybrid fuzzy rough set model was pro-posed in the early 1990’s, many ...
Abstract In this paper, a general framework for the study of dual fuzzy rough approximation operator...
This work was partially supported by the Spanish Ministry of Science and Technology under Project TI...
AbstractWe propose a new fuzzy rough set approach which, differently from most known fuzzy set exten...
Approximation operators play a vital role in rough set theory. Their three elements, namely, binary ...
Approximation operators play a vital role in rough set theory. Their three elements, namely, binary ...
AbstractThis paper focuses on the generalization of covering-based rough set models via the concept ...
The starting point of the paper is the (well-known) observation that the classical Rough Set Theory ...
In fuzzy rough sets a fuzzy T-similarity relation is employed to describe the degree of similarity b...
AbstractThe primitive notions in rough set theory are lower and upper approximation operators define...
The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulatio...