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	The research of the genetic algorithm combined with chromosome fitness to optimize the flatness error evaluation
	Guo, Yingdi ; Wu, Weicong ; Jiang, Mijia ; Li, Bonan ; Fang, Bingbing ; Gao, Xing ; Gao X(高兴)
	2013
关键词	Chromosomes Computational geometry Computer simulation Errors Health Reverse engineering
英文摘要	Conference Name:2012 International Conference on Mechatronics and Control Engineering, ICMCE 2012. Conference Address: Guangzhou, China. Time:November 29, 2012 - November 30, 2012.; Queensland University of Technology, Australia; Korea Maritime University; Hong Kong Industrial Technology Research Centre; Inha University, Korea; This paper suggests an improved genetic algorithm to seek the minimum range value in the ideal-plane flatness measurement. This algorithm increases measurement accuracy by using dynamic cross factor, mutation factor and a new concept called chromosome fitness. It was proved in simulation experiments that its accuracy is better than other flatness error evaluating algorithms like the minimal territory evaluating algorithm and the computational geometry algorithm etc. So it can be used for measuring industrial production components error and verifying assumed models in reverse engineering etc. ? (2013) Trans Tech Publications, Switzerland.
语种	英语
出处	http://dx.doi.org/10.4028/www.scientific.net/AMM.278-280.1342
出版者	Trans Tech Publications
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/87111]
专题	医学院－会议论文
推荐引用方式 GB/T 7714	Guo, Yingdi,Wu, Weicong,Jiang, Mijia,et al. The research of the genetic algorithm combined with chromosome fitness to optimize the flatness error evaluation. 2013-01-01.

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