We use the notion of the rough set diagram introduced by Wasilewska and Vigneron 8] to present a general decision procedure for validity of equations in rough boolean algebra. First, we establish equivalence of validity in rough boolean algebra to validity in so called simple rough boolean algebra. Second, we propose a decision method for simple rough boolean algebra, which is to construct and ...

Rough set theory is a very effective tool to deal with granularity and vagueness in information systems. Covering-based rough set theory is an extension of classical rough set theory. In this paper, firstly we present the characteristics of the reducible element and the minimal description covering-based rough sets through downsets. Then we establish lattices and topological spaces in coveringb...

The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The pap...

Rough set theory provides a systematic way for rule extraction, attribute reduction and knowledge classification in information systems. Some measurements are important in rough sets. For example, information entropy, knowledge dependency are useful in attribute reduction algorithms. This paper proposes the concepts of the lower and upper covering numbers to establish measurements in covering-b...

Rough set theory is a relatively new mathematical tool for use in computer applications in circumstances which are characterized by vagueness and uncertainty. In this paper, applications of inclusion degree in rough set theory are discussed, the relationships among inclusion degree, measures on rough set theory and some generalized rough set models are established. These results will be very he...

To keep the key idea of rough set and the representation of information in rough set theory, empty representation is processed properly and three new forms of rough approximation sets are defined as a generation of general binary relation based rough set model. Moreover, the properties of approximation operators in these new rough sets are discussed. The relations among them are studied in this...

We outline a rough–neuro computing model as a basis for granular computing. Our approach is based on rough sets, rough mereology and information granule calculus.

The main objective of this special issue is to present readers with the significantly extended and improved versions of the articles presented at the International Conference on Rough Sets, Fuzzy Sets, and Granular Computing (RSFDGrC’05) held in Regina, Canada in September 2005. In the standard rough set model, the lower and upper approximations are defined based on the two extreme cases (full ...

This paper presents and compares two views of the theory of rough sets. The operator-oriented view interprets rough set theory as an extension of set theory with two additional unary operators. Under such a view, lower and upper approximations are related to the interior and closure operators in topological spaces, the necessity and possibility operators in modal logic, and lower and upper appr...