粒子群聚类算法综述

聚类分析是数据挖掘的重要技术之一，它能够通过无监督的学习过程发现隐藏的模式，具有独立发现知识的能力。对现有文献中基于粒子群优化算法的聚类分析技术作了全面的介绍，对几种主要的粒子群聚类算法的基本原理及其特点进行了总结,并分析比较了它们的优点和不足，概述了粒子群聚类算法的常见应用领域；最后探讨了粒子群聚类算法进一步的研究方向。

Survey of particle swarm clustering algorithms

Clustering analysis is one of the important data mining techniques that can discover hidden modes by unsupervised learning and has the ability of acquiring knowledge independently. This paper presented an all-around introduction of PSO-based clustering methods in existing literatures, described the basic principles and the characteristics of the existing popular particle swarm clustering algorithms, and made the comparison about their merits and demerits. Then summarized the applications of particle swarm clustering algorithms. Finally, pointed out the future research directions of particle swarm clustering algorithms.