首页> 外文会议>IEEE International Conference on Industrial Engineering and Engineering Management >An effective particle swarm optimization method for data clustering.
【24h】

An effective particle swarm optimization method for data clustering.

机译:一种用于数据聚类的有效粒子群优化方法。

获取原文

摘要

Data clustering analysis is generally applied to image processing, customer relationship management and product family construction. This paper applied Particle Swarm Optimization (PSO) algorithm on data clustering problems. Two reflex schemes are implemented on PSO algorithm to improve the efficiency. The proposed methods were tested on seven datasets, and their performance is compared with those of PSO, K-means and two other clustering methods. Results show that our schemes are both robust and suitable for solving data clustering problems.
机译:数据聚类分析通常应用于图像处理,客户关系管理和产品系列建设。本文应用了粒子群优化(PSO)算法数据集群问题。在PSO算法上实现了两个反射方案以提高效率。在七个数据集中测试了所提出的方法,将它们的性能与PSO,K-Means和另外两种聚类方法进行比较。结果表明,我们的方案既具有稳健,适合解决数据聚类问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号