| 模糊C-均值聚类算法的改进研究 |
| |
| 引用本文： | 朱长江,张缨.模糊C-均值聚类算法的改进研究[J].河南大学学报(自然科学版),2012,42(1):92-95. |
| |
| 作者姓名： | 朱长江 张缨 |
| |
| 作者单位： | 河南大学计算中心,河南开封,475001 |
| |
| 摘 要： | 模糊C-均值聚类算法通过迭代的爬山技术来寻找问题的最优解,是一种局部搜索算法,容易受初始值的影响而陷入局部极小值.遗传算法是一种应用广泛的全局优化算法,是一种与求解问题无关的算法模式,能够有效解决模糊C-均值聚类算法对初始化敏感的问题,利用改进后的遗传算法能更好地解决聚类问题.
|
| 关 键 词： | 模糊C-均值聚类 遗传算法 种群划分 |
Research of Improved Fuzzy C-Means Clustering Algorithm |
| |
| ZHU Chang-jiang
,
ZHANG Ying.Research of Improved Fuzzy C-Means Clustering Algorithm[J].Journal of Henan University(Natural Science),2012,42(1):92-95. |
| |
| Authors: | ZHU Chang-jiang ZHANG Ying |
| |
| Institution: | (Computing center,Henan University,Henan Kaifeng 475001,China) |
| |
| Abstract: | The fuzzy C-means clustering algorithm climbing through iterative techniques to find the optimal solution is a local search algorithm,vulnerable to the effects of the initial value into a local minimum.Genetic algorithm is a widely used global optimization algorithms,and solving problems is a model-independent algorithm,can effectively solve the fuzzy C-means clustering algorithm to initialize the sensitive issue,the use of improved genetic algorithm to better clustering solution. |
| |
| Keywords: | fuzzy C-means clustering genetic algorithm population division |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
