In this paper, an adaptive genetic algorithm be present , it solve disadvantages of K-Means by combine parallel genetic algorithm, evolving flow and adaptive.

In this paper, an adaptive genetic algorithm be present, it solve disadvantages of K-Means by combine parallel genetic algorithm, evolving flow and adaptive.

In this paper, we combine the concept of the adaptive with Genetic algo- rithms to approach the evolvement of nature, and try to change the fixed probability of ...

In this paper we analyze the image compression problem using genetic clustering algorithms based on the pixels of the image. The main problem to solve is to ...

This study combines Adaptive Genetic Algorithm, K-Means and Greedy Selection to solve clustering problem, named RAGKA. In first step, the centroid is ...

In this paper we fully describe the grouping genetic algorithm for clustering, starting with the proposed encoding, different modifications of crossover and ...

To improve the efficiency of solving large-scale TSPs, this work presents a novel adaptive layered clustering framework with improved genetic algorithm (ALC_IGA) ...

A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this article. The searching capability of genetic algorithms is ...

An adaptive genetic algorithm is a type of evolutionary computing algorithm that uses genetic operations such as reproduction, crossover, and mutation

To overcome the difficulty of finding good parameter values, adaptive GAs have been developed [20]. A self-adaptive genetic algorithm for clustering (SAGA) ...