常天庆, 李勇, 杨国振, 张雷. 并行小生境粒子群优化的模糊聚类算法[J]. 微电子学与计算机, 2014, 31(1): 13-16.
引用本文: 常天庆, 李勇, 杨国振, 张雷. 并行小生境粒子群优化的模糊聚类算法[J]. 微电子学与计算机, 2014, 31(1): 13-16.
CHANG Tian-qing, LI Yong, YANG Guo-zhen, ZHANG Lei. Fuzzy Clustering Algorithm Based on Parallel Niches Particle Swarm Optimization[J]. Microelectronics & Computer, 2014, 31(1): 13-16.
Citation: CHANG Tian-qing, LI Yong, YANG Guo-zhen, ZHANG Lei. Fuzzy Clustering Algorithm Based on Parallel Niches Particle Swarm Optimization[J]. Microelectronics & Computer, 2014, 31(1): 13-16.

并行小生境粒子群优化的模糊聚类算法

Fuzzy Clustering Algorithm Based on Parallel Niches Particle Swarm Optimization

  • 摘要: 针对模糊聚类算法对初始聚类中心敏感、容易陷入局部最优的问题,采用并行小生境粒子群优化算法对模糊聚类算法进行改进.通过山谷函数对小生境进行识别以形成互斥的多个子群,采用惩罚函数实现多子群并行搜索过程中的信息共享机制,引入混合聚类有效性函数获取最佳聚类数.仿真结果表明,该算法能提高模糊聚类算法的搜索效率以及分类精度.

     

    Abstract: Because fuzzy clustering algorithm is sensitive to initial cluster center and easy to fall into local optimum,improved fuzzy clustering algorithm based on parallel niches particle swarm optimization algorithm is presented in this paper.Valley function is used to form mutually exclusive subswarms by identifying niches.Punishment function is adopted to realize information sharing mechanism in the process of subswarms parallel searching.Hybrid cluster validity function is imported to obtain optimal cluster number.Simulation results show that the improved algorithm can enhance searching efficiency and classification accuracy of fuzzy clustering algorithm.

     

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