This article puts forward a clustering center selecting algorithm based on quantum harmonic oscillator model (CCSA-QHOM).The algorithm describes the way of data objects finding center of the cluster in clustering problem by taking the change of wave function's probability in the process of high energy level to a lower energy level for theoretical model.It can quickly find the optimal number of clusters and cluster center

computing time has nothing to do with the size of the data set after the dataset being got in grid space.Experiments show that CCSA-QHOM is more suitable for processing the clustering center selection question of dataset in which grid density distribution of each subclass haves a single peak characteristic.