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. |
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