一种基于竞争型群体优化的数据聚类方法

doi:10.3969/j.issn.1006-2475.2019.01.014

计算机与现代化

一种基于竞争型群体优化的数据聚类方法

(1.华南理工大学广州学院计算机工程学院,广东广州510800;2.湖南科技大学计算机科学与工程学院,湖南湘潭411201)

收稿日期:2018-09-05 出版日期:2019-01-30 发布日期:2019-01-30
作者简介:秦映波(1978-),男,湖南岳阳人,副教授,硕士,研究方向:智能信息处理,E-mail: 59494223@qq.com; 通信作者:曹步清(1979-),男,副教授,博士,CCF会员(20532M),研究方向:面向服务的软件工程; 邓春晖(1963-),男,副教授,硕士,研究方向:大数据,物联网。
基金资助:
国家自然科学基金资助项目(61772193,61702181); 广东省普通高校特色创新类项目(2015KTSCX183); 湖南省自然科学基金资助项目(2017JJ2098)

A Data Clustering Method Based on Competitive Swarm Optimizer

(1. Department of Computer Engineering, Guangzhou College of South China University of Technology, Guangzhou 510800, China;
2.School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

Received:2018-09-05 Online:2019-01-30 Published:2019-01-30

摘要/Abstract

摘要： 数据聚类在智能信息处理中具有非常重要的作用。传统的数据聚类方法，如K-means算法，存在对初始聚类中心敏感等问题。随着智能优化算法的发展，人们用智能优化算法进行数据聚类取得了一定的效果，但存在容易陷入局部最优等问题。为此，本文将在高维优化问题中取得良好效果的竞争型群体优化算法中引入数据聚类，利用竞争型群体优化算法强大的全局探索能力搜索聚类中心进行数据聚类，在UCI的5个数据集上的实验结果表明竞争型群体优化算法比遗传算法、粒子群算法不仅能得到更好的聚类效果，而且收敛性能更好。

关键词: 聚类, 竞争型群体优化, UCI数据集

Abstract: Data clustering plays a very important role in intelligent information processing, but the traditional K-means algorithm is sensitive to initial clustering centers. With the development of intelligent optimization algorithm, people uses intelligent optimization algorithm to cluster data and achieve a certain effect, but it is still easy to fall into the local optimization. In this paper, the competitive swarm optimizer algorithm which has achieved good results in high dimensional optimization problem is exploited for data clustering, the powerful exploration ability of competitive swarm optimizer is used to search clustering centers for data clustering. The experimental results on the five data sets of UCI show that the competitive swarm optimizer can not only get better clustering effect but also better convergence performance than genetic algorithm and particle swarm optimization algorithm.

Key words: clustering, competitive swarm optimizer, UCI dataset

中图分类号:

TP311

秦映波1,曹步清2,邓春晖1. 一种基于竞争型群体优化的数据聚类方法[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2019.01.014.

QIN Ying-bo1, CAO Bu-qing2, DENG Chun-hui1. A Data Clustering Method Based on Competitive Swarm Optimizer[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.01.014.

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一种基于竞争型群体优化的数据聚类方法

A Data Clustering Method Based on Competitive Swarm Optimizer

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