Clustering Analysis Based on Chaos Genetic Algorithm

摘要：

To improve the accuracy of clustering classification, the Chaos Genetic Algorithm was proposed. In this algorithm, the ergodic property of chaos phenomenon is used to optimize the initial population, so it can accelerate the convergence of Genetic Algorithms. Chaotic systems are sensitive to initial condition system parameters. In order to escape from local optimums, the chaos operator was applied to optimize the individuals after the process of selection operator, crossover operator and mutation operator. Theory and experiment shows that the algorithm can get global optimum clustering center, and greatly improve the amplitude of operation.

关键词： Chaos genetic algorithm cluster classification

作者: Shengzhou Wang Yanbin Wu

作者单位: School of Management, China University of Mining and Technology, Xuzhou 221116, China School of Busi National Laboratory of Coal Resources and Mine Safety, China University of Mining and Technology, Be

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 16-19

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）