Extensions and intentions in the rough set theory
Information Sciences: an International Journal
Relational interpretations of neighborhood operators and rough set approximation operators
Information Sciences—Informatics and Computer Science: An International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A Generalized Definition of Rough Approximations Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
On Generalizing Pawlak Approximation Operators
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Information Sciences—Informatics and Computer Science: An International Journal
Reduction and axiomization of covering generalized rough sets
Information Sciences: an International Journal
An axiomatic characterization of a fuzzy generalization of rough sets
Information Sciences—Informatics and Computer Science: An International Journal
On Three Types of Covering-Based Rough Sets
IEEE Transactions on Knowledge and Data Engineering
The algebraic structures of generalized rough set theory
Information Sciences: an International Journal
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Toward a generalized theory of uncertainty (GTU)--an outline
Information Sciences: an International Journal
Granular computing: structures, representations, and applications
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Covering-Based generalized rough fuzzy sets
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Tolerance Approximation Spaces
Fundamenta Informaticae
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Rough set theory is a powerful tool for dealing with uncertainty, granularity, and incompleteness of knowledge in information systems. In this paper we study covering-based rough fuzzy sets in which a fuzzy set can be approximated by the intersection of some elements in a covering of the universe of discourse. Some properties of the covering-based fuzzy lower and upper approximation operators are examined. We present the conditions under which two coverings generate the same covering-based fuzzy lower and upper approximation. We approximate fuzzy sets based on a binary relation and its properties are introduced. Finally, we establish the equivalency between rough fuzzy sets generated by a covering and rough fuzzy sets generated by a binary relation.