【摘要】 数据聚类是数据挖掘中的一个重要课题。聚类问题可以归结为一个优化问题。蚁群算法作为一种鲁棒性很强的优化算法具有很强的全局优化能力。该文给出了一种并行多种群自适应蚁群算法。该算法采用多种群并行搜索,并在种群中采用基于目标函数值的启发式信息素分配策略和根据目标函数自动调整蚂蚁搜索路径的行为。理论分析和仿真实验表明,该算法是非常有效的。更多还原

【Abstract】 Cluster analysis is a kind of unsupervised learning method.Clustering can be regarded as a optimization problem.Ant colony algorithms are a novel category of evolutionary computing methods for optimization problems.A parallel adaptive ant colony algorithm is proposed in this paper to solve the cluster problem.Theoretical analysis and experiments show this method is faster and more efficient to converge upon the optimal value in the whole field.更多还原