基于文化算法的混合聚类方法

New hybrid clustering algorithm based on cultural algorithms

文化算法是一种新的进化计算方法,文化进化过程除了具有传统的进化计算模型的群体空间外,还增加了一个知识空间和支持这两个空间通信的机制。以文化算法为框架,采用K-均值模型为聚类模型,针对聚类问题设计适用于该问题的知识空间、群体空间、接受函数和影响函数,提出一种混合聚类算法KCAGA。实验证明,该算法对解决聚类问题初始化敏感以及容易陷入局部优化取得很好的效果,适用于聚类问题的解决。

Cultural Algorithms is an new evolutionary model.The algorithm is dual inheritance systems that besides the population component which traditional evolutionary computation methods have,there is an additional peer component belief space and a supporting communication mechanism between those two components.This paper proposes a new hybrid clustering algorithm KCAGA,the algorithm takes the cultural algorithm as a frame,uses the K-Means Algorithm as clustering model,and designs knowledge space,population space,accept function,influence function for special clustering problem.Experiments show that this algorithm can not only avoid the disadvantages of the classical K-Means clustering algorithm,but also has greater searching capability globally.The new algorithm achieves good results to resolve the cluster problem.