In this paper, we take a GL-quantale as the truth value table to study a new rough set model—L-valued fuzzy rough sets. The three key components of this model are: an L-fuzzy set A as the universal set, an L-valued relation of A and an L-fuzzy set of A (a fuzzy subset of fuzzy sets). Then L-valued fuzzy rough sets are completely characterized via both constructive and axiomatic approaches. 

The whole mathematical scenario has changed with the advent of the Rough Set Theory, a powerful tool to deal with uncertainty and incompleteness of knowledge in information system. With the advancement of research, the Soft Set Theory has emerged as an advanced mathematical tool to deal with data associated with uncertainty. The present chapter endeavors to forge a connection between soft set a...

There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information system, the realization of rough set approximation operation has two major steps, firstly convert the information system from multiple valued one to single valued formal context, s...

In Rough Set Theory, dependency in the knowledge base is an important aspect when drawing inferences about the world. Rough set (inexact set) is defined by using a fixed binary relation (equivalence relation, tolerance relation, similarity relation, etc) to analyze vague, imprecise, inexact problems, which satisfy many interesting properties. The neighborhood based rough set theory is an extens...

Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. The classical rough set theory based on equivalence relation has made a great progress, while the equivalence relation is too harsh to meet and is extended to dominance relation in real world. It is important to investigate rough computational methods for rough set theory, which is one of the bottleneck problems...

Rough set theory was proposed by Pawlak for analyzing data and reasoning about data. From a concept analysis point of view, we review and reformulate main results of rough set theory in the context of data processing and analysis. This enables us to see clearly the motivations for introducing rough set theory and its basic components and appropriate applications, leading to an appreciation for ...

Rough set theory was proposed by Pawlak for analyzing data and reasoning about data. From a concept analysis point of view, we review and reformulate main results of rough set theory in the context of data processing and analysis. This enables us to see clearly the motivations for introducing rough set theory and its basic components and appropriate applications, leading to an appreciation for ...

Problem of knowledge analysis for decision support system is the most difficult task of information systems. This paper presents a new approach based on notions of mathematical theory of Rough Sets to solve this problem. Using these concepts a systematic approach has been developed to reduce the size of decision database and extract reduced rules set from vague and uncertain data. The method ha...

The theory of rough sets is an extension of set theory with two additional unary set-theoretic operators deened based on a binary relation on the universe. These two operators are related to the modal operators in modal logics. By exploring the relationship between rough sets and modal logics, this paper proposes and examines a number of extended rough set models. By the properties satissed by ...