关键词: 微粒群算法, 聚类, 山峰函数, 小生境

Abstract: A mountain clustering algorithm based on particle swarm optimization is constructed in this paper by combining the two algorithm of mountain clustering and particle swarm optimization. Firstly, the grid is built in the data space, then a mountain function denoting the density of data is made, and lastly, the operation of razing out the mountains orderly to find clustering centers is replaced by NichePSO algorithm. All global maximums of mountain function are found by running NichPSO algorithm, and the centers number and position are found at same time. The simulating experiments indicate that the new algorithm can offset some limitation of traditional clustering algorithms.

Key words: Particle swarm optimization, Clustering, Mountain function, Niching