一种基于简单遗传算法的K-Means改进算法

针对k-means算法对初始值敏感、易陷入局部极小值等缺点，结合遗传算法的思想，提出了一种基于遗传算法和k-means算法的混合聚类方法，为了测试该聚类算法的性能，用k-means 算法和改进的算法进行了1组实验，并对2种算法的聚类结果进行比较，实验结果表明算法能够有效地解决聚类问题.

Improved K-Means Algorithm Based on a Simple Genetic Algorithm

K-means algorithm is sensitive to initial value,easy to fall into local minimum value.In response to these shortcomings,the idea of genetic algorithm is proposed based on genetic algorithm and k-means algorithm for hybrid clustering method.In order to test the performance of clustering algorithm,a set of experiments are conducted by using k-means algorithm and the improved algorithm,and the clustering results by the two algorithms are compared.It is showed that the clustering algorithm can effectively solve the clustering problem.