| 基于遗传算法的聚类分析 |
| |
| 引用本文： | 傅景广,许刚,王裕国.基于遗传算法的聚类分析[J].计算机工程,2004,30(4):122-124. |
| |
| 作者姓名： | 傅景广 许刚 王裕国 |
| |
| 作者单位： | 中国科学院软件研究所,北京,100080 |
| |
| 摘 要： | 给出了一种基于遗传算法的聚类分析方法。采用二进制编码方式对聚类的中心进行编码，并用特征向量与相应聚类中心的欧氏距离的和来判断聚类划分的质量，通过选择、交叉和变异操作对聚类中心的编码进行优化，得到便聚类划分效果最好的聚类中心。实验结果显示，该方法的聚类划分效果明显优于传统的K-均值方法。
|
| 关 键 词： | 遗传算法 聚类 K-均值算法 二进制编码 |
| 文章编号： | 1000-3428(2004)04-0122-03 |
Clustering Based on Genetic Algorithm |
| |
| FU Jingguang,XU Gang,WANG Yuguo.Clustering Based on Genetic Algorithm[J].Computer Engineering,2004,30(4):122-124. |
| |
| Authors: | FU Jingguang XU Gang WANG Yuguo |
| |
| Abstract: | A clustering method based on genetic algorithm is presented. The cluster centers are binary encoded. The sum of the Euclidean distances of the points from their respective cluster centers is adopted as the similarity metric. The optimal cluster centers are searched by selection, crossover and mutation. Experimental results demonstrate that GA-based clustering is better than K-means algorithm. |
| |
| Keywords: | Genetic algorithm Clustering K-means algorithm Binary encoding |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
