Add to ORKGAbstract We introduce linguistic rough set (LRS) by integrating linguistic quantifiers in the rough set frame-work. The proposed LRS is inspired by the ways in which humans process imprecise information. It operates directly with the linguistic summaries and caters to imprecision implicit in the real world with partial knowledge. The measures of LRS are developed and its properties are investigated in detail. An approach is proposed for approximation of fuzzy concepts with the proposed LRS. This approach is applied in a real world case-study on the credit scoring analysis problem
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
In this paper, we present some new ideas for fuzzy reasoning from the viewpoint of fuzzy rough set. ...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...
Abstract. We provide a new approach to synthesis of Formal Concept Analysis and Rough Set Theory. In...
F~zzy sets theory and fuzzy logic constitute the basis for the l inguist ic approach. Under this app...
Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision ma...
In the article the problem of imprecise information and concepts is considered. The theory of rough ...
Abstract—Rough set theory is a popular and powerful machine learning tool. It is especially suitable...
Rough set theory and fuzzy logic are mathematical frameworks for granular computing forming a theore...
We present a new representation for linguistic hedges using a framework of fuzzy rough sets. In trad...
Abstract. In this work, we analyze how the linguistic labels of a lin-guistic variable can be a usef...
The concept of a fuzzy set was introduced by Zadeh in 1965. Fuzzy set is a mathematical model of vag...
Abstract. New concepts of rough natural number systems are intro-duced in this research paper from b...
Data used in machine learning applications is prone to contain both vague and incomplete information...
An integration between the theories of fuzzy sets and rough sets has been attempted by providing a m...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
In this paper, we present some new ideas for fuzzy reasoning from the viewpoint of fuzzy rough set. ...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...
Abstract. We provide a new approach to synthesis of Formal Concept Analysis and Rough Set Theory. In...
F~zzy sets theory and fuzzy logic constitute the basis for the l inguist ic approach. Under this app...
Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision ma...
In the article the problem of imprecise information and concepts is considered. The theory of rough ...
Abstract—Rough set theory is a popular and powerful machine learning tool. It is especially suitable...
Rough set theory and fuzzy logic are mathematical frameworks for granular computing forming a theore...
We present a new representation for linguistic hedges using a framework of fuzzy rough sets. In trad...
Abstract. In this work, we analyze how the linguistic labels of a lin-guistic variable can be a usef...
The concept of a fuzzy set was introduced by Zadeh in 1965. Fuzzy set is a mathematical model of vag...
Abstract. New concepts of rough natural number systems are intro-duced in this research paper from b...
Data used in machine learning applications is prone to contain both vague and incomplete information...
An integration between the theories of fuzzy sets and rough sets has been attempted by providing a m...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
In this paper, we present some new ideas for fuzzy reasoning from the viewpoint of fuzzy rough set. ...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...