An application of particle swarm optimization algorithm to clustering analysis

作者：Kuo R J^*; Wang M J; Huang T W

来源：Soft Computing, 2011, 15(3): 533-542.

DOI：10.1007/s00500-009-0539-5

• Clustering analysis
• Particle swarm optimization algorithm
• K-means

Particle swarm optimization algorithm (PSOA), which maintains a population of particles, where each particle represents a potential solution to an optimization problem, is a population-based stochastic search process. This study intends to integrate PSOA with K-means to cluster data. It is shown that PSOA can be employed to find the centroids of a user-specified number of clusters. The proposed PSOA is evaluated using four data sets, and compared to the performance of some other PSOA-based methods and K-means method. Computational results show that the proposed method has much potential. A real-world problem for order clustering also illustrates that the proposed method is quite promising.

• 出版日期2011-3