Customer segmentation application of PSO parallel cluster
微粒群并行聚类在客户细分中的应用

The paper presented the parallel cluster algorithm of adaptive particle swarm optimization, which adopted task parallelization and partial asynchronous communication to decrease the computing time. The proposed algorithm combined the fast search optimum ability of parallel particle swarm optimization with parameters dynamical optimization property of adaptive. It could maintain the individual diversity and restrain the degenerate phenomenon. Finally, the presented algorithm was used to analyze the telecom customer segmentation. The experiments indicate the presented algorithm on the cluster maintains pre-ferable accuracy, the speed-up and scaled-up.