Predicting chain dimensions from an artificial neural network model

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	Predicting chain dimensions from an artificial neural network model
	Zhang, LX ; Xia, A ; Zhao, DL
刊名	JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS
	2000-12-01
卷号	38 期号:23 页码:3163-3167
关键词	Artificial Neural Network Characteristic Ratio Polymers
ISSN号	0887-6266
英文摘要	Artificial neural network models are used to investigate polymer chain dimensions. In our model, the input nodes are glass transition temperature (T-g), entanglement molecular weight (M-e), and melt density (rho). The number of nodes in the hidden layer is eight. We found that the relative error for prediction of the characteristic ratio ranges from 0.77 to 7.5% and that the overall average error is 3.57%. Artificial neural network models may provide a new method for studying statistics properties of polymer chains. (C) 2000 John Wiley & Sons, Inc.
语种	英语
出版者	JOHN WILEY & SONS INC
WOS记录号	WOS:000165258000016
内容类型	期刊论文
源URL	[http://ir.iccas.ac.cn/handle/121111/75679]
专题	中国科学院化学研究所
通讯作者	Zhang, LX
作者单位	1.Zhejiang Univ, Dept Phys, Hangzhou 310028, Peoples R China 2.Chinese Acad Sci, Inst Chem, Ctr Mol Sci, Polymer Phys Lab, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Zhang, LX,Xia, A,Zhao, DL. Predicting chain dimensions from an artificial neural network model[J]. JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS,2000,38(23):3163-3167.
APA	Zhang, LX,Xia, A,&Zhao, DL.(2000).Predicting chain dimensions from an artificial neural network model.JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS,38(23),3163-3167.
MLA	Zhang, LX,et al."Predicting chain dimensions from an artificial neural network model".JOURNAL OF POLYMER SCIENCE PART B-POLYMER PHYSICS 38.23(2000):3163-3167.