clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

A rapid genetic algorithm based on chaos mechanism is presented in this paper. We introduced the chaos mechanism into the genetic algorithm to remedy the defect of premature convergence in the genetic algorithm, then continuously compressed the searching intervals of the optimization variable for increasing convergence speed. Experiments indicate that this method is a rapid and effective evolut...

Today the Genetic Algorithm (GA) is used to solve a large variety of complex nonlinear optimization problems. However, permute convergence which is one of the most important disadvantages in GA is known to increase the number of iterations for reaching a global optimum. This paper, presents a new GA based on chaotic systems to overcome this shortcoming,. We employ logistic map and tent map as t...

Genetic algorithm is an evolutionary algorithm. It is particularly suitable for solving NP-complete optimization problems. In this paper, we propose a rapid genetic algorithm based on chaos mechanism. We introduce the chaos mechanism into the genetic algorithm. Using the ergodic property of the chaos movement, this method can remedy the defect of premature convergence in the genetic algorithm. ...

This contribution presents the results of an investigation on deterministic spatiotemporal chaos control by means of evolutionary algorithms. Three evolutionary algorithms are used for chaos control: differential evolution, self-organizing migrating algorithm and genetic algorithm. Models of spatiotemporal chaos, so called coupled map lattices, are used. The main aim of this investigation was t...

In this paper, chaos based a new arithmetic crossover operator on the genetic algorithm has been proposed. The most frequent issue for the optimization algorithms is stuck on problem's defined local minimum points and it needs excessive amount of time to escape from them; therefore, these algorithms may never find global minimum points. To avoid and escape from local minimums, a chaotic arithme...

The main idea of developing Grid is to make effective use of the computation power distributed all over the world. Economical issues are the most vital motivations of resource owners to share their services. This means that users are required to pay for access to services based on their usage and level of QoS they need. Therefore total cost of executing an application is becoming one of the mos...

Chaos based communications have drawn increasing attention over the past years. Chaotic signals are derived from non-linear dynamic systems. They are aperiodic, broadband and deterministic signals that appear random in the time domain. Because of these properties, chaotic signals have been proposed to generate spreading sequences for wide-band secure communication recently. Like conventional DS...