Improvement of the Genetic Algorithm and Its Application on Clustering

摘要：

This paper proposes an improved genetic algorithm, it keeps the population diversity by similarity checks on the population before selection, and the algorithm solves the early-maturing problem of the population evolution,and proposes a formula for mutation probabifity related with similarity rate and iteration times. The algorithm not only maintains a good diversity of population, but also guarantees the algorithm convergence. Compared to c-means clustering algorithm, the improved genetic algorithm proposed in this paper has been proved its improvement effect by the result of clustering experiments using the UCI datasets of WINE and IRIS.

关键词： early maturity population diversify similarity several crossovers adaptive mutation probability

作者: Chen Rui Zou Shurong Zhang Hongwei Feng Zhongtian

作者单位: Department of Computer, Chengdu University of Information Technology, Chengdu 610225

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 1575-1577

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）