An Efficient Hybrid Data Clustering based on Genetic and Particle Swarm Optimization Algorithms
In this paper, the authors focus on two very similar evolutionary algorithms those are Genetic Algorithm (GA), Particle Swarm Optimization (PSO). The genetic algorithm which is widely used in data mining technology was proposed,, PSO is more used to solve the optimization problems.. This paper first gives a brief introduction to these two EA techniques to highlight the common computational procedures. To make advantage of both PSO and GA, they combined the both algorithms, i.e. the output obtained by clustering the data sets with genetic algorithms is given as input to the PSO.