In data mining clustering techniques are used to group together the objects showing similar characteristics within the same cluster and the objects demonstrating different characteristics are grouped into clusters. Clustering approaches can be classified into two categories namelyHard clustering and Soft clustering. In hard clustering data is divided into clusters in such a way that each data i...

We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster va...

We introduce the notions of anti fuzzy right ideal, anti fuzzy right k-ideal and intuitionistic fuzzy right k-ideal of semirings. We investigate the their properties and connections with right k-ideal, fuzzy right k-ideal, anti fuzzy right k-ideal. We characterize regular semiring through intuitionistic fuzzy right ideal. The semi regularity of semirings is characterized by intuitionistic fuzzy...

In this paper, a subtractive relational fuzzy c-medoids clustering approach is discussed to identify web user session clusters from weblogs, based on their browsing behavior. In this approach, the internal arrangement of data along with the density of pairwise dissimilarity values is favored over arbitrary starting estimations of medoids as done in the conventional relational fuzzy c-medoids al...

K. T. Atanassov, ?Intuitionistic fuzzy sets?, Fuzzy Sets and Systems, 20(1986), 87-96. S. S. Benchalli and Jenifer J. Karnel, ?On fuzzy b open sets in fuzzy topological spaces?, J. Comp. & Math. Sci, 1(2010), 127 – 134. C. L. Chang, ?Fuzzy topological spaces?, J. Math. Anal. Appl, 24(1968), 182-190. D. Coker, ?An introduction to intuitionistic fuzzy topological spaces?, Fuzzy Sets and Systems, ...

This paper presents a detailed study and comparison of some Kernelized Fuzzy C-means Clustering based image segmentation algorithms Four algorithms have been used Fuzzy Clustering, Fuzzy CMeans(FCM) algorithm, Kernel Fuzzy CMeans(KFCM), Intuitionistic Kernelized Fuzzy CMeans(KIFCM), Kernelized Type-II Fuzzy CMeans(KT2FCM).The four algorithms are studied and analyzed both quantitatively and qual...

This paper mainly intends to discuss the solution of fully fuzzy linear systems (FFLS) Ax + b = Cx + d, where A and C are fuzzy matrices, b and d are fuzzy vectors. We transform the systems by using fuzzy numbers with a new parametric form for finding a fuzzy vector x that satisfies in the system.

An approach to fuzzy control based on fuzzy logic in narrow sense (fuzzy inference rules + fuzzy set of logical axioms) is proposed. This gives an interesting theoretical framework and suggests new tools for fuzzy control. c © 2001 Elsevier Science B.V. All rights reserved.