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计算机工程 ›› 2007, Vol. 33 ›› Issue (23): 16-18. doi: 10.3969/j.issn.1000-3428.2007.23.006

• 博士论文 • 上一篇    下一篇

基于克隆选择的快速动态聚类算法

张 旭1,2,郭 晨2   

  1. (1. 大连交通大学机械工程学院,大连 116028;2. 大连海事大学自动化与电气工程学院,大连 116026)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-05 发布日期:2007-12-05

Fast Dynamic Clustering Algorithm Based on Clone Selection

ZHANG Xu1,2, GUO Chen2   

  1. (1. School of Mechanical Engineering, Dalian Jiaotong University, Dalian 116028; 2. School of Automation and Electrical Engineering, Dalian Maritime University, Dalian 116026)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-05 Published:2007-12-05

摘要: 为了在聚类数不确定的情况下实现聚类分析,通过借鉴生物免疫系统中的克隆选择原理并结合聚类有效性分析,提出了一种基于克隆选择的快速动态聚类算法。该算法可以根据样本数据自动确定聚类数目及中心位置,克服了传统聚类算法容易陷入局部极小值、对初始值敏感的缺点。通过引入新算子及适当选取聚类的初始中心,使算法的收敛速度明显提高,仿真实验结果表明了本算法的有效性。

关键词: 克隆选择原理, 聚类有效性分析, 动态聚类

Abstract: In order to achieve cluster analysis with unknown number of clusters, this paper proposes a fast dynamic clustering algorithm based on clone selection, which is inspired by the clone selection principle of the vertebrate immune system and combines the cluster validity analysis. It not only adaptively determines the amount and the center’s positions of clustering, but also avoids the local optima and the flaw about sensitive to the initialization. The convergence speed of this algorithm is improved obviously through introducing a new search operation and selecting appropriate initial clustering center. Experimental results indicate the validity of the proposed algorithm.

Key words: clone selection principle, cluster validity analysis, dynamic clustering

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