A Model Based on Bootstrapped Neural Networks for Modeling the Removal of Organic Compounds by Nanofiltration and Reverse Osmosis Membranes
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://link.springer.com/article/10.1007/s13369-018-3484-8/fulltext.html
Reference37 articles.
1. Lin, Y.-L.: Effects of organic, biological and colloidal fouling on the removal of pharmaceuticals and personal care products by nanofiltration and reverse osmosis membranes. J. Membr. Sci. 542, 342–351 (2017). https://doi.org/10.1016/j.memsci.2017.08.023
2. Verliefde, A.R.; Heijman, S.G.; Cornelissen, E.R.; Amy, G.; Van der Bruggen, B.; van Dijk, J.C.: Influence of electrostatic interactions on the rejection with NF and assessment of the removal efficiency during NF/GAC treatment of pharmaceutically active compounds in surface water. Water Res. 41(15), 3227–3240 (2007). https://doi.org/10.1016/j.watres.2007.05.022
3. Verliefde, A.R.D.; Cornelissen, E.R.; Heijman, S.G.J.; Verberk, J.Q.J.C.; Amy, G.L.; Van der Bruggen, B.; van Dijk, J.C.: The role of electrostatic interactions on the rejection of organic solutes in aqueous solutions with nanofiltration. J. Membr. Sci. 322(1), 52–66 (2008). https://doi.org/10.1016/j.memsci.2008.05.022
4. Gur-Reznik, S.; Koren-Menashe, I.; Heller-Grossman, L.; Rufel, O.; Dosoretz, C.G.: Influence of seasonal and operating conditions on the rejection of pharmaceutical active compounds by RO and NF membranes. Desalination 277(1–3), 250–256 (2011). https://doi.org/10.1016/j.desal.2011.04.029
5. Ammi, Y.; Khaouane, L.; Hanini, S.: Prediction of the rejection of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes using neural networks. Korean J. Chem. Eng. 32(11), 2300–2310 (2015). https://doi.org/10.1007/s11814-015-0086-y
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