Application of ANN back-propagation for Fracture Design Parameters of Middle Carbon Steel in Extra-low Cycle Bend Torsion Loading

doi:10.4028/www.scientific.net/AMM.345.272

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	Application of ANN back-propagation for Fracture Design Parameters of Middle Carbon Steel in Extra-low Cycle Bend Torsion Loading
	Duan, HongYan; Li, YouTang; Sun, ZhiJia; Zhang, YangYang
	2013
关键词	Artificial Neural Networks Extra-low Cycle Middle Carbon Steel Bend Torsion Fatigue
卷号	345
DOI	10.4028/www.scientific.net/AMM.345.272
页码	272-276
英文摘要	The fracture problems of medium carbon steel (MCS) under extra-low cycle bend torsion loading were studied using artificial neural networks (ANN) in this paper. The training data were used in the formation of training set of ANN. The ANN model exhibited excellent comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. It is possible to claim that, ANN is fairly promising prediction technique if properly used.
会议录	ADVANCED RESEARCH ON MECHANICAL ENGINEERING, INDUSTRY AND MANUFACTURING ENGINEERING III
会议录出版者	TRANS TECH PUBLICATIONS LTD
会议录出版地	LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND
语种	英语
WOS研究方向	Engineering ; Materials Science
WOS记录号	WOS:000327902800061
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36895]
专题	学报编辑部机电工程学院
通讯作者	Duan, HongYan
作者单位	Lanzhou Univ Technol, Coll Mechanoelect Engn, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Duan, HongYan,Li, YouTang,Sun, ZhiJia,et al. Application of ANN back-propagation for Fracture Design Parameters of Middle Carbon Steel in Extra-low Cycle Bend Torsion Loading[C]. 见:.