一种基于变长字符串的遗传聚类方法

Z. Bin, Gan Zhi-chun, Huang Qiangqiang
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引用次数: 0

摘要

本文提出了一种基于变长字符串遗传算法的聚类问题解决方法。该方法通过变长染色体的遗传操作生成最优解,自动确定最合适的聚类中心个数,有效解决了现有K-means聚类算法高度受初始聚类中心约束、需要指定具体聚类中心个数等缺陷。实验结果和对比表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Genetic Clustering Method Based on Variable Length String
This paper proposes a method based on variable length string genetic algorithm to solve the clustering problem. This method generates the optimal solution by genetic operation of variable length chromosomes, automatically determines the most appropriate number of cluster centers, and effectively solves the existing K-means clustering algorithms’ defects such as highly subject to the constraint of the initial clustering centers and need to specify the specific number of clustering centers. The experimental results and comparison show that the purposed method’s effectiveness.
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