Soft set theory is provided as a general mathematical tool for dealing with uncertainties. At
present, it is very important to put forward some decision making methods based on (fuzzy) …

Decision trees have been widely used in data mining and machine learning as a
comprehensible knowledge representation. Minimal cost decision tree construction plays a …

This paper investigates roughness of fuzzy soft sets. A pair of fuzzy soft rough
approximations is proposed and their properties are given. Based on fuzzy soft rough …

This paper proposes a novel approach to decision making based on grey relational analysis
and MYCIN certainty factor, which describes decision making problems with fuzzy soft sets …

Rough sets and soft sets are important tools to deal with uncertainties. Combining rough
sets and soft sets, we apply rough soft set theory to BCI-algebras. Some basic operations of …

By means of Dubois and Prade's idea, we apply rough fuzzy sets and fuzzy rough sets to
algebraic structures. The concepts of rough fuzzy strong h-ideals (rough fuzzy prime ideals) …

The notions of fuzzy 1-type (2-type) positive implicative filter and fuzzy normal filter of
pseudo-BCK algebras are introduced, some properties and equivalent conditions are given …

The relationships between T-rough sets and covering based rough sets are investigated,
and two kinds of generated methods of rough approximation operators from existing rough …

Molodtsov introduced the concept of soft set as a new mathematical tool for dealing with
uncertainties. Recently, Cagman and Enginoglu [16] provided new definitions and …

Attribute reduction of information system is one of the most important applications of rough
set theory. This paper focuses on generalized decision system and aims at studying positive …