A Novel Approach of Order Clustering using Combination of Particle Swarm Optimization and Genetic Algorithm

Abstract

To extract some useful and meaningful information from the large volume of dataset is known as learning. Learning can be
classified as supervised and non-supervised learning. Clustering comes under the category of the unsupervised. Genetic
algorithm (GA) and Particle swarm optimization (PSO) are two well-known method of clustering. Premature convergence is
most common problem associated with the PSO. This paper address this problem and suggest a method to overcome this
problem of PSO for using in order clustering. Simulation results shows that he proposed method outperform the existing
methods.