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This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find agood or near-optimal solution in reasonable time, but we show that its performancemay be improved by seeding the initial swarm with the result of the c-meansalgorithm. Various clustering simulations are experimentally compared with the FCMalgorithm in order to illustrate the efficiency and ability of the proposed algorithms.

This paper analyzes a linear system of equations when the righthandside is a fuzzy vector and the coefficient matrix is a crisp M-matrix. Thefuzzy linear system (FLS) is converted to the equivalent crisp system withcoefficient matrix of dimension 2n × 2n. However, solving this crisp system isdifficult for large n because of dimensionality problems . It is shown that thisdifficulty may be avoided by computing the inverse of an n×n matrix insteadof Z^{−1}.

In this paper, the notion of almost S^{*}-compactness in L-topologicalspaces is introduced following Shi’s definition of S^{*}-compactness. The propertiesof this notion are studied and the relationship between it and otherdefinitions of almost compactness are discussed. Several characterizations ofalmost S^{*}-compactness are also presented.

Fuzzy rough n-ary subhypergroups are introduced and characterized.

The aim of this paper is to present the new and interesting notionof ascending family of $alpha $−n-norms corresponding to an intuitionistic fuzzy nnormedlinear space. The notion of best aproximation sets in an $alpha $−n-normedspace corresponding to an intuitionistic fuzzy n-normed linear space is alsodefined and several related results are obtained.

In this paper the concept of metacompactness in L-topologicalspaces is introduced by means of point finite families of L-fuzzy sets. Thisfuzzy metacompactness is a natural generalization of Lowen fuzzy compactness.Further a characterization of fuzzy metacompactness in the weakly inducedL-topological spaces is also obtained.

In this paper, we propose a new definition of intuitionistic fuzzyquasi-metric and pseudo-metric spaces based on intuitionistic fuzzy points. Weprove some properties of intuitionistic fuzzy quasi- metric and pseudo-metricspaces, and show that every intuitionistic fuzzy pseudo-metric space is intuitionisticfuzzy regular and intuitionistic fuzzy completely normal and henceintuitionistic fuzzy normal. These are the intuitionistic fuzzy generalization ofthe corresponding properties of fuzzy quasi-metric and pseudo- metric spaces.

In this paper we study two important concepts, i.e. the direct andthe inverse limit of hyperstructures associated with fuzzy sets of type 2, andshow that the direct and the inverse limit of hyperstructures associated withfuzzy sets of type 2 are also hyperstructures associated with fuzzy sets of type 2.

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