A study on water quality prediction by a hybrid CNN-LSTM model with attention mechanism
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-021-14687-8.pdf
Reference45 articles.
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4. Chai T, Draxler RR (2014) Root mean square error (rmse) or mean absolute error (mae)?–arguments against avoiding rmse in the literature. Geosci Model Dev 7(3):1247–1250. https://doi.org/10.5194/gmd-7-1247-2014
5. Chang F-J, Kao L-, Kuo Y-M, Liu C-W (2010) Artificial neural networks for estimating regional arsenic concentrations in a blackfoot disease area in taiwan. J Hydrol 388(1-2):65–76. https://doi.org/10.1016/j.jhydrol.2010.04.029
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