An Effective Hybrid Approach to Data Clustering Using Genetic Algorithm and Hunting Search Algorithm

One of the approaches to analyze a high volume of data accurately, is to use clustering algorithm. The goal of clustering is to gain a set of data and dividing them to different groups and clusters. Due to the wide searching area , offering an efficient algorithm by which it would be possible to reduce the time of clustering have been always considered by researchers and was recognized as one of the challenges in this process. In this paper a new algorithm to clustering sets of data is offered which is based on genetic algorithm and Search hunting algorithm on a set of real UCI data shows that this algorithm has significantly better performance in terms of duration and quality of clustering compared to the typical clustering algorithm.

کلیدواژه ها:

data clustering ، hunting Search algorithm ، Meta-heuristic algorithm ، Denotative clustering