A generalized hybrid unsupervised learning algorithm, which is termed as rough-fuzzy possibilistic c-means (RFPCM), is proposed in this paper. It comprises a judicious integration of the principles of rough and fuzzy sets. While the concept of lower and upper approximations of rough sets deals with uncertainty, vagueness, and incompleteness in class definition, the membership function of fuzzy ...

In this paper we extend some previously established links between the derivation operators used in formal concept analysis and some mathematical morphology operators to fuzzy concept analysis. We also propose to use mathematical morphology to navigate in a fuzzy concept lattice and perform operations on it. Links with other lattice-based formalisms such as rough sets and F-transforms are also e...

In this paper we propose a fuzzy rule generation approach based on granular computing using rough mereology (FRGAGCRM). The proposed system works in two phases. In the first phase, the pre-processing phase which use fuzzification methodology which map the numeric dataset into categorical dataset according to membership function described in this paper. In other hand, the second phase consists o...

Facial expressions being a part of gesture is a biggest asset for non verbal communication. We are using facial expression of current image as a context to hand gesture which again acts as a context to the next image linking the images in a video to extract unstable sentiments. Facial expression is not precise as beauty. It’s a vague concept; hence we have used Rough set. But some facial expres...

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,...