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	The Research of the Genetic Algorithm Combined with Chromosome Fitness to Optimize the Flatness Error Evaluation
	YingdiGuo ; WeicongWu ; MijiaJiang ; BonanLi ; BingbingFang ; Xing Gao
	2013
关键词	Genetic Algorithm Chromosome Fitness Flatness Measurement Smart Evaluation of Flatness
英文摘要	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.
语种	英语
出版者	Applied Mechanics and Materials
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/79869]
专题	OAPS－大学生创新计划项目
推荐引用方式 GB/T 7714	YingdiGuo,WeicongWu,MijiaJiang,et al. The Research of the Genetic Algorithm Combined with Chromosome Fitness to Optimize the Flatness Error Evaluation[J],2013.
APA	YingdiGuo,WeicongWu,MijiaJiang,BonanLi,BingbingFang,&Xing Gao.(2013).The Research of the Genetic Algorithm Combined with Chromosome Fitness to Optimize the Flatness Error Evaluation..
MLA	YingdiGuo,et al."The Research of the Genetic Algorithm Combined with Chromosome Fitness to Optimize the Flatness Error Evaluation".(2013).

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