| 基于改进的粒子群优化的模糊C-均值聚类算法 |
| |
| 引用本文： | 王杨.基于改进的粒子群优化的模糊C-均值聚类算法[J].计算机与数字工程,2014,42(9):1610-1612. |
| |
| 作者姓名： | 王杨 |
| |
| 作者单位： | 辽宁石油化工大学计算机与通信工程学院 抚顺113001 |
| |
| 摘 要： | 利用粒子群优化（PSO）算法全局寻优的特点,很大程度上避免了模糊C-均值聚类（FCM）算法对初值敏感、易陷入局部收敛的缺陷.利用收敛速度快的K均值聚类法得到的聚类中心作为PSO算法初始聚类中心的参考,提出一种新的模糊C-均值聚类算法Improved PSO FCM.实验结果表明,论文算法提高了FCM的搜索能力,聚类更为准确,效率更高.
|
| 关 键 词： | 粒子群优化算法 模糊C-均值聚类算法 初始聚类中心 K均值算法 |
Fuzzy C-means Clustering Algorithm Based on Improved Particle Swarm Optimization |
| |
| WANG Yang.Fuzzy C-means Clustering Algorithm Based on Improved Particle Swarm Optimization[J].Computer and Digital Engineering,2014,42(9):1610-1612. |
| |
| Authors: | WANG Yang |
| |
| Affiliation: | WANG Yang (School of Computer and Communication Engineering, Liaoning University of Petroleum and Chemical Technology, Fushun 113001) |
| |
| Abstract: | The fuzzy C-means clustering algorithm has the problems of local optimal value and sensitivity to initial values, which are overcomed by particle swarm optimization algorithm with the global optimization. A new fuzzy C-means clustering algorithm, Improved PSO FCM is proposed with the clustering centers obtained by K-means algorithm as the reference of the searching scope of PSO algorithm. The experimental results show the algorithm improves the searching capacity of FCM, and is more accurate and efficient. |
| |
| Keywords: | PSO FCM initial clustering center K-means algorithm |
| 本文献已被 维普 万方数据 等数据库收录！ |
