QQ客服 官方微博 反馈留言

	Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies (EI收录)
	Shi, Bin[1]; Wang, Peng[1,2]; Jiang, Jiping[1,3]; Liu, Rentao[1]
刊名	Science of the Total Environment
	2018
卷号	610-611页码:1390-1399
关键词	Backpropagation Financial data processing Neural networks Soil conservation Surface waters Time series Water conservation Water management Water quality Wavelet decomposition
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2169196
专题	华南理工大学
作者单位	1.[1] School of Environment, Harbin Institute of Technology, Harbin 2.150090, China 3.[2] State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 4.150090, China 5.[3] School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 6.518055, China
推荐引用方式 GB/T 7714	Shi, Bin[1],Wang, Peng[1,2],Jiang, Jiping[1,3],等. Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies (EI收录)[J]. Science of the Total Environment,2018,610-611:1390-1399.
APA	Shi, Bin[1],Wang, Peng[1,2],Jiang, Jiping[1,3],&Liu, Rentao[1].(2018).Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies (EI收录).Science of the Total Environment,610-611,1390-1399.
MLA	Shi, Bin[1],et al."Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies (EI收录)".Science of the Total Environment 610-611(2018):1390-1399.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。