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Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
Prediction of potentially toxic elements in water resources using MLP-NN, RBF-NN, and ANFIS: a comprehensive review
JC Agbasi, JC Egbueri - Environmental Science and Pollution Research, 2024 - Springer
Water resources are constantly threatened by pollution of potentially toxic elements (PTEs).
In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) …
In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) …
Design and Machine Learning Prediction of In Situ Grown PDA-Stabilized MOF (UiO-66-NH2) Membrane for Low-Pressure Separation of Emulsified Oily Wastewater
Significant progress has been made in designing advanced membranes; however,
persistent challenges remain due to their reduced permeation rates and a propensity for …
persistent challenges remain due to their reduced permeation rates and a propensity for …
[HTML][HTML] Crystal violet removal using ZIF-60: Batch adsorption studies, mechanistic & machine learning modeling
This study, for the first time, reported the utilization of ZIF-60 for the adsorptive removal of
organic pollutant from contaminated water. Characterization techniques were used to …
organic pollutant from contaminated water. Characterization techniques were used to …
New-generation machine learning models as prediction tools for modeling interfacial tension of hydrogen-brine system
Abstract Recently, hydrogen (H 2) gas has gained prodigious attention as a sustainable
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …
Machine learning predictive insight of water pollution and groundwater quality in the Eastern Province of Saudi Arabia
This study presents an innovative approach for predicting water and groundwater quality
indices (WQI and GWQI) in the Eastern Province of Saudi Arabia, addressing critical …
indices (WQI and GWQI) in the Eastern Province of Saudi Arabia, addressing critical …
Hydrophilic, oleophilic and switchable Janus mixed matrix membranes for oily wastewater treatment: A review
Purification of oily wastewater holds significant importance due to its detrimental
environmental and human health implications. Mixed matrix membranes (MMMs) have …
environmental and human health implications. Mixed matrix membranes (MMMs) have …
Advancements in ceramic membranes for robust oil-water separation
This paper provides a comprehensive review of the recent advancements in ceramic
membrane technology specifically tailored for oil-water separation. With the increasing …
membrane technology specifically tailored for oil-water separation. With the increasing …
Insight into soft chemometric computational learning for modelling oily-wastewater separation efficiency and permeate flux of polypyrrole-decorated ceramic-polymeric …
Reliable modeling of oily wastewater emphasizes the paramount importance of sustainable
and health-conscious wastewater management practices, which directly aligns with the …
and health-conscious wastewater management practices, which directly aligns with the …
[HTML][HTML] Synthesis and application of MgCuAl-layered triple hydroxide/carboxylated carbon nanotubes/bentonite nanocomposite for the effective removal of lead from …
A novel multicomponent adsorbent nano-composite was synthesized by intercalating
bentonite clay and carboxylated carbon nanotubes (CNT-COOH) into MgCuAl-layered triple …
bentonite clay and carboxylated carbon nanotubes (CNT-COOH) into MgCuAl-layered triple …