he fuzzy set introduced by L.A.Zadeh [16] in 1965 and the rough set introduced by Pawlak [12] in 1982 are generalizations of the classical set theory. Both these set theories are new mathematical tool to deal the uncertain, vague, imprecise and inexact data. In Zadeh fuzzy set theory, the degree of membership of elements of a set plays the key role, whereas in Pawlak rough set theory, the equiv...

Fuzzy rule interpolation is an important technique for performing inferences with sparse rule bases. Even when given observations have no overlap with the antecedent values of any rule, fuzzy rule interpolation may still derive a conclusion. Nevertheless, fuzzy rule interpolation can only handle fuzziness but not roughness. Rough set theory is a useful tool to deal with incomplete knowledge, wh...

The concept of classifying the records of the information system has been due to Two Way Approach [ ie, lower and upper approximations ] of Pawlak’s rough sets model. But the approximation does to take into consideration the degree of contribution of the basic categories. This deficiency was eliminated in early nineties by Ziarko who has proposed VPRS model and later on various efforts were mad...

One main drawback of intrusion detection system is the inability of detecting new attacks which do not have known signatures. In this paper we discuss an intrusion detection method that proposes independent component analysis (ICA) based feature selection heuristics and using rough fuzzy for clustering data. ICA is to separate these independent components (ICs) from the monitored variables. Rou...

It goes without saying that a challenging quest for the construction of intelligent systems is realized through the development of hybrid information technologies and their vigorous and prudent exploitation. In a nutshell, what has emerged under the name of computational intelligence (CI) or soft computing is a well-orchestrated, highly synergistic consortium of technologies of neural networks,...

This paper is two folded. In first fold, the authors have illustrated the interplay among fuzzy, rough, and soft set theory and their way of handling vagueness. In second fold, the authors have studied their individual strengths to discover association rules. The performance of these three approaches in discovering comprehensible rules are presented. Usage of Fuzzy, Rough, and Soft Set Approach...

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 ...

Data usually exists with hybrid formats in real-world applications, and a unified data reduction for hybrid data is desirable. In this paper a unified information measure is proposed to computing discernibility power of a crisp equivalence relation and a fuzzy one, which is the key concept in classical rough set model and fuzzy rough set model. Based on the information measure, a general defini...