Iranian journal of fuzzy systems
Volume:5 Issue: 3, Oct2008

This paper presents an efficient hybrid method, called fuzzy particle swarm optimization (FPSO), based on the particle swarm optimization (PSO) and fuzzy c-means (FCM) algorithms in order to solve the fuzzy clustering problem, especially for large sizes. When the problem becomes larger, the FCM algorithm may result uneven distribution of data and it is so hard to find an optimal solution in reasonable time. We use the PSO algorithm to find a good or near-optimal solution in reasonable time. To further improve the performance the PSO clustering algorithm, this paper considers seeding of the initial swarm with the result of the c-means algorithm. Various clustering simulations are experimentally compared with the FCM algorithm in order to show the efficiency and ability of the proposed algorithms

This paper analyzes the system of equations that right-hand side is a fuzzy vector and the coefficient matrix is a crisp M-matrix. We convert the fuzzy linear system (FLS) to the equivalent crisp system with coefficient matrix of dimension 2n×2n. But solving the crisp system is difficult because of its huge dimension (2n×2n) for large n. In this paper we employ a method which scape from it, i.e. instead of computing Z-1, we compute the inverse of a matrix which is n × n.

In this paper, the notion of almost S*-compactness is introduced in L-topological spaces based on S*-compactness. Its properties are discussed and the relations between it and other almost compactness are discussed. Moreover many characterizations of almost S*-compactness are presented

The aim of this paper is to present a new and interesting notion of ascending family of $\alpha-n$-norms corresponding to intuitionistic fuzzy n-normed linear space. Further, best aproximation sets in $\alpha-n$-normed space corresponding to intuitionistic fuzzy n-normed linear space is introduced and we provide some interesting results on it.

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 point. We prove some properties of intuitionistic fuzzy quasi-metric and pseudo-metric spaces, and prove that every intuitionistic fuzzy pseudo-metric space is intu- itionistic fuzzy regular and every intuitionistic fuzzy pseudo-metric space is intuitionistic fuzzy completely normal and so is intuitionistic fuzzy normal, which are the intuitionistic fuzzy generalization of the similar properties of fuzzy quasi-metric and pseudo-metric space.

We analyse here two important notions: the direct and the inverse limit of hyperstructures associated with fuzzy sets of type 2. More exactly, we 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.