Using ant swarm intelligence for data clustering analysis

In this paper we present a new algorithm that uses the new swarm intelligence based techniques to investigate clustering. The algorithm, called CASI, combines a smart exploratory strategy based on ant colonies that locate the objects in a cluster with the probability, which is updated by the pheromone, while the rule of updating pheromone is according to total within cluster variance. We have applied this algorithm on two synthetic data and we have measured, through computer simulation, the proposed algorithm outperforms several existing approaches such as GCA, SOM.