New clustering algorithm based on evolutionary computation
Xiaojun Wu · Computer Engineering and Applications Journal · 2011
Cluster analysis which plays an important role in data mining,is widely used.It has important value both in theo-ry and application.Considering the stability of the genetic algorithm and the local searching capability of particle swarm opti-mization in clustering,the two algorithms are combined.Particle swarm optimization operators are implemented after the cross-over and mutation operators,and GAPSO clustering algorithm is put forwarded.Simulation results are given to illustrate the stability and convergence of the proposed method.GAPSO is proved to be easier to carry out,faster to converge and more stable than other methods.