基于遗传算法和CLARANS的一种改进聚类算法

An Optimized Clustering Algorithm Based on Genetic Algorithm and CLARANS

阐述了CLARANS(Clustering Large Applications based on RANdomized Search-基于随机搜索的大规模应用聚类)聚类算法的工作原理,同时为了解决CLARANS聚类挖掘算法效率低,费时长等问题,本文将遗传算法的思想引入CLAR-ANS算法,利用遗传算法的隐并行性对其进行改进,提出一种GA-CLARANS算法,有效地降低了聚类所花费的时间。实验证明GA-CLARANS算法在运行效率方面相比CLARANS算法有较好的表现,是可行且有效的。

The theory of CLARANS is introduced, and an improved algorithm based on genetic algorithm is proposed to solve the problem that efficiency of CLARANS algorithm is low. The new algorithm is called GA-CLARANS. Simulation shows that this algorithm can solve the problem. It is feasible and efficient.