Iranian Journal of Fuzzy Systems
Year:2008 | Volume:5 | Issue:3|Papers Count:8

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

This paper analyzes a linear system of equations when the right and side is a fuzzy vector and the coefficient matrix is a crisp M-matrix. The fuzzy linear system (FLS) is converted to the equivalent crisp system with coefficient matrix of dimension 2n x 2n. However, solving this crisp system is difficult for large n because of dimensionality problems. It is shown that this difficulty may be avoided by computing the inverse of an n x n matrix instead of Z-1.

In this paper, the notion of almost S*-compactness in L-topological spaces is introduced following Shi's definition of S*-compactness. The properties of this notion are studied and the relationship between it and other definitions of almost compactness are discussed. Several characterizations of almost S*-compactness are also presented.

Fuzzy rough n-ary subhyper groups are introduced and characterized

The aim of this paper is to present the new and interesting notion of ascending family of a- n-norms corresponding to an intuitionistic fuzzy nnormed linear space. The notion of best aproximation sets in an a- n-normed space corresponding to an intuitionistic fuzzy n-normed linear space is also defined and several related results are obtained.

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

In this paper, we propose a new definition of intuitionistic fuzzy quasi-metric and pseudo-metric spaces based on intuitionistic fuzzy points. We prove some properties of intuitionist fuzzy quasi- metric and pseudo-metric spaces, and show that every intuitionist fuzzy pseudo-metric space is intuitionist fuzzy regular and intuitionistic fuzzy completely normal and hence intuitionistic fuzzy normal. These are the intuitionistic fuzzy generalization of the corresponding properties of fuzzy quasi-metric and pseudo- metric spaces.

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