A Survey of Machine and Deep Learning Applications in the Assessment of Water Quality-Reference-Cited by-同舟云学术

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A Survey of Machine and Deep Learning Applications in the Assessment of Water Quality

Published:2024 Issue: Volume: Page:471-483
ISSN:2199-7373
Container-title:World Sustainability Series
language:en
Short-container-title:

Author:

Azrour Mourade,Dargaoui Souhayla,Mabrouki Jamal,Guezzaz Azidine,Benkirane Said,Shafik Wasswa,Ahmad Sultan

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-56292-1_38

Reference67 articles.

1. Nwankwo, C.B., Hoque, M.A., Islam, M.A., Dewan, A.: Groundwater constituents and trace elements in the basement aquifers of Africa and sedimentary aquifers of Asia: medical hydrogeology of drinking water minerals and toxicants. Earth Syst. Environ. 4, 369–384 (2020)

2. Mancuso, G., Bencresciuto, G.F., Lavrnić, S., Toscano, A.: Diffuse water pollution from agriculture: a review of nature-based solutions for nitrogen removal and recovery. Water 13(14), 1893 (2021)

3. Yusuf, M., Purwandani, I.: Ecological politics of water: the ramifications of tourism development in Yogyakarta. South East Asia Res. 28(3), 327–343 (2020)

4. Fattah, G., Elouardi, M., Benchrifa, M., Ghrissi, F., Mabrouki, J.: Modeling of the coagulation system for treatment of real water rejects. In Advanced Technology for Smart Environment and Energy, Springer, pp. 161–171 (2023)

5. Mabrouki, J. et al.: Geographic information system for the study of water resources in Chaâba El Hamra, Mohammedia (Morocco). In Artificial Intelligence and Smart Environment: ICAISE’2022, Springer, pp. 469–474 (2023)

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1. Sustainable Development;Advances in Hospitality, Tourism, and the Services Industry;2024-07-26

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