Abstract: In order to solve the problems that the general antcolony clustering algorithm expenses a long time and easily produces redundant number of clusters，a new multi-loading ant colony clustering algorithm based on dynamic neighborhood is provided.The algorithm seeks for the pure neighborhood through the neighborhood dynamic auto-adapted adjustment，enhances ant’s memory to store the size of the pure neighborhood，exchanges the information between ants，multi-loads and merges the similar regions to form the final cluster result.Experiment shows that the new algorithm effectively advances the efficiency of algorithm and the result of clustering.

Key words: ant colony clustering algorithm, dynamic neighborhood, multi-load

摘要： 针对基本蚁群聚类算法较长时间开销和易产生冗余聚类数目的缺陷，提出了一种基于动态邻域的多载蚁群聚类算法。算法通过邻域动态自适应调整寻找纯净的邻域，增强蚂蚁记忆体记忆纯净邻域的大小，蚂蚁之间协同交流进行多载整合相似邻域形成最终聚类结果。实验结果表明新算法能有效提高算法效率且取得较好的聚类效果。

关键词: 蚁群聚类算法, 动态邻域, 多载