A Hybrid Machine Learning Model for Modeling Nitrate Concentration in Water Sources
Author:
Publisher
Springer Science and Business Media LLC
Subject
Pollution,Water Science and Technology,Ecological Modeling,Environmental Chemistry,Environmental Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11270-023-06745-3.pdf
Reference39 articles.
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2. Adeloju, S. B., Khan, S., & Patti, A. F. (2021). Arsenic contamination of groundwater and its implications for drinking water quality and human health in under-developed countries and remote communities—A review. Applied Sciences, 11(4), 1926.
3. Alabool, H. M., et al. (2021). Harris hawks optimization: a comprehensive review of recent variants and applications. Neural computing and applications, 33(15), 8939–8980.
4. Amiri, S., Rajabi, A., Shabanlou, S., Yosefvand, F., & Izadbakhsh, M. A. (2023) Prediction of groundwater level variations using deep learning methods and GMS numerical model. Earth Science Informatics. https://doi.org/10.1007/s12145-023-01052-1
5. Azizpour, A., Izadbakhsh, M. A., Shabanlou, S., Yosefvand, F., & Rajabi, A. (2021). Estimation of water level fluctuations in groundwater through a hybrid learning machine. Groundwater for Sustainable Development, 15, 100687. https://doi.org/10.1016/j.gsd.2021.100687
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