Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation
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/s11356-021-13875-w.pdf
Reference31 articles.
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3. Anand, A., & Suganthi, L. (2020). Forecasting of electricity demand by hybrid ANN-PSO models. In Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications (pp. 865-882). IGI Global.
4. Avila R, Horn B, Moriarty E, Hodson R, Moltchanova E (2018) Evaluating statistical model performance in water quality prediction. J Environ Manag 206:910–919
5. Bisht, A. K., Singh, R., Bhatt, A., & Bhutiani, R. (2017). Development of an automated water quality classification model for the River Ganga. In International Conference on Next Generation Computing Technologies (pp. 190-198). Springer, Singapore.
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