Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A comparative study of fuzzy rough sets
Fuzzy Sets and Systems
Information Sciences—Informatics and Computer Science: An International Journal
A fuzzy soft set theoretic approach to decision making problems
Journal of Computational and Applied Mathematics
Information Sciences: an International Journal
Applications of soft sets in ideal theory of BCK/BCI-algebras
Information Sciences: an International Journal
Computers & Mathematics with Applications
Computers & Mathematics with Applications
The normal parameter reduction of soft sets and its algorithm
Computers & Mathematics with Applications
On some new operations in soft set theory
Computers & Mathematics with Applications
A combined forecasting approach based on fuzzy soft sets
Journal of Computational and Applied Mathematics
Combination of interval-valued fuzzy set and soft set
Computers & Mathematics with Applications
The parameterization reduction of soft sets and its applications
Computers & Mathematics with Applications
A comparative study of fuzzy sets and rough sets
Information Sciences: an International Journal
Journal of Computational and Applied Mathematics
Soft rough sets based on similarity measures
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
The parameter reduction of fuzzy soft sets based on soft fuzzy rough sets
Advances in Fuzzy Systems
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Fuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing with uncertainties and are closely related. Feng et al. introduced the notions of rough soft set, soft rough set and soft rough fuzzy set by combining fuzzy set, rough set and soft set all together. This paper is devoted to the further discussion of the combinations of fuzzy set, rough set and soft set. A new soft rough set model is proposed and its properties are derived. Furthermore, fuzzy soft set is employed to granulate the universe of discourse and a more general model called soft fuzzy rough set is established. The lower and upper approximation operators are presented and their related properties are surveyed.