Ensemble hybrid machine learning to simulate dye/divalent salt fractionation using a loose nanofiltration membrane

N Baig, SI Abba, J Usman, M Benaafi… - Environmental Science …, 2023 - pubs.rsc.org
The escalating quantity of wastewater from multiple sources has raised concerns about both
water reuse and environmental preservation. Therefore, there is a pressing need for …

Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction

N Baig, J Usman, SI Abba, M Benaafi… - Journal of Cleaner …, 2023 - Elsevier
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …

Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater

SK Bhagat, KE Pilario, OE Babalola, T Tiyasha… - Journal of Cleaner …, 2023 - Elsevier
A wide range of dyes are being disposed in water bodies from several industrial runoff and
the quantity is rapidly increasing over the years. From an environmental safety point of view …

Prediction of organic contaminant rejection by nanofiltration and reverse osmosis membranes using interpretable machine learning models

T Zhu, Y Zhang, C Tao, W Chen, H Cheng - Science of The Total …, 2023 - Elsevier
Efficiency improvement in contaminant removal by nanofiltration (NF) and reverse osmosis
(RO) membranes is a multidimensional process involving membrane material selection and …

[HTML][HTML] Evaluating the efficiency of nanofiltration and reverse osmosis membranes for the removal of micro-pollutants using a machine learning approach

P Masuodi, F Bahmanzadegan, A Hemmati… - Case Studies in …, 2024 - Elsevier
Water removal research is a critical study area across diverse industries and scientific
domains. This investigation evaluates three prominent machine learning models including …

Nanocomposite ceramic membranes as novel tools for remediation of textile dye waste water–A review of current applications, machine learning based modeling and …

JM Solaiman, N Rajamohan, M Yusuf… - Journal of Environmental …, 2024 - Elsevier
Textile effluent treatment has gained significant attention due to the carcinogenic effects of
the dye pollutants present and their enhanced resistance to degradation. Porous ceramic …

Pilot-scale evaluation of nanofiltration and reverse osmosis for process reuse of segregated textile dyewash wastewater

E Kurt, DY Koseoglu-Imer, N Dizge, S Chellam… - Desalination, 2012 - Elsevier
Segregated wastewaters from dyewash processes in a weaving industry were treated for
decolorization, as well as the removal of chemical oxygen demand and salts using a pilot …

Integrated Modeling of Hybrid Nanofiltration/Reverse Osmosis Desalination Plant Using Deep Learning-Based Crow Search Optimization Algorithm

SI Abba, J Usman, I Abdulazeez, DU Lawal, N Baig… - Water, 2023 - mdpi.com
The need for reliable, state-of-the-art environmental investigations and pioneering
approaches to address pressing ecological dilemmas and to nurture the sustainable …

Multivariate data-based optimization of membrane adsorption process for wastewater treatment: Multi-layer perceptron adaptive neural network versus adaptive …

SA Naghibi, E Salehi, M Khajavian, V Vatanpour… - Chemosphere, 2021 - Elsevier
Application of machine-learning methods to assess the batch adsorption of malachite green
(MG) dye on chitosan/polyvinyl alcohol/zeolite imidazolate frameworks membrane …

Modelling dye removal by adsorption onto water treatment residuals using combined response surface methodology-artificial neural network approach

MR Gadekar, MM Ahammed - Journal of environmental management, 2019 - Elsevier
In this study, response surface methodology (RSM)–artificial neural network (ANN)
approach was used to optimise/model disperse dye removal by adsorption using water …