Accurate Prediction of Reverse Solute Flux in Forward Osmosis Systems Using Comparative Machine Learning Models
Author:
Funder
University of Hail
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13369-024-09267-0.pdf
Reference47 articles.
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3. Boubakri, A.; Elgharbi, S.; Dhaouadi, I.; Mansour, D.; Al-Tahar Bouguecha, S.: Optimization and prediction of lead removal from aqueous solution using FO–MD hybrid process: statistical and artificial intelligence analysis. J. Environ. Manag. 337, 117731 (2023). https://doi.org/10.1016/j.jenvman.2023.117731
4. Reddy, B.S.; Maurya, A.K.; Narayana, P.L.; Kori, S.A.; Sung, H.; Reddy, M.R.; Cho, K.K.; Sharada, Y.S.; Reddy, N.S.: Modeling the relationship between forward osmosis process parameters and permeate flux. Sep. Purif. Technol. 300, 121830 (2022). https://doi.org/10.1016/j.seppur.2022.121830
5. Ben Maouia, D.; Boubakri, A.; Hafiane, A.; Bouguecha, S.: Aluminum sulfate as an innovative draw solute for forward osmosis desalination. Chem. Afr. 3, 141–152 (2020). https://doi.org/10.1007/s42250-019-00092-9
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