Notice of RetractionHybrid adaptive niche to improve particle swarm optimization clustering algorithm

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Clustering is an important data analysis and data mining technique. PSO clustering is one of the popular partition algorithm. But it often suffers from the problem of premature convergence and traps in suboptimum solution. This paper uses adaptive niche particle swarm algorithm to improve clustering. And it is also studied the impact of different fitness optimization function to clustering data. The results show that the algorithm which hybrids adaptive niche to PSO clustering techniques has more competitive. It also shows that the new fitness optimization function we proposed is more promising in the fields of high dimension data set and large difference of the number samples in clusters than the popular function of Merwe introduced.