Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects
G Alam, I Ihsanullah, M Naushad… - Chemical Engineering …, 2022 - Elsevier
Artificial intelligence (AI) has emerged as a powerful tool to resolve real-world problems and
has gained tremendous attention due to its applications in various fields. In recent years, AI …
has gained tremendous attention due to its applications in various fields. In recent years, AI …
Machine learning in natural and engineered water systems
R Huang, C Ma, J Ma, X Huangfu, Q He - Water Research, 2021 - Elsevier
Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …
sustainable development. To better protect the water environment and conserve water …
Tackling environmental challenges in pollution controls using artificial intelligence: A review
This review presents the developments in artificial intelligence technologies for
environmental pollution controls. A number of AI approaches, which start with the reliable …
environmental pollution controls. A number of AI approaches, which start with the reliable …
Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research
The presence of various forms of heavy metals (HMs)(eg, Cu, Cd, Pb, Zn, Cr, Ni, As, Co, Hg,
Fe, Mn, Sb, and Ce) in water bodies and sediment has been increasing due to industrial and …
Fe, Mn, Sb, and Ce) in water bodies and sediment has been increasing due to industrial and …
A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence
M Fan, J Hu, R Cao, W Ruan, X Wei - Chemosphere, 2018 - Elsevier
Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients,
heavy metals and persistent organic pollutants. For the modeling and optimization of …
heavy metals and persistent organic pollutants. For the modeling and optimization of …
Facile synthesis of economical feasible fly ash–based zeolite–supported nano zerovalent iron and nickel bimetallic composite for the potential removal of heavy …
GKR Angaru, YL Choi, LP Lingamdinne, JS Choi… - Chemosphere, 2021 - Elsevier
Heavy metals contamination of water is one of the environmental issue globally. Thus
prepared fly ash–based zeolite (FZA)–supported nano zerovalent iron and nickel (nZVI/Ni …
prepared fly ash–based zeolite (FZA)–supported nano zerovalent iron and nickel (nZVI/Ni …
Predicting aqueous adsorption of organic compounds onto biochars, carbon nanotubes, granular activated carbons, and resins with machine learning
Predictive models are useful tools for aqueous adsorption research; existing models such as
multilinear regression (MLR), however, can only predict adsorption under specific …
multilinear regression (MLR), however, can only predict adsorption under specific …
Predicting Cu (II) adsorption from aqueous solutions onto nano zero-valent aluminum (nZVAl) by machine learning and artificial intelligence techniques
Predicting the heavy metals adsorption performance from contaminated water is a major
environment-associated topic, demanding information on different machine learning and …
environment-associated topic, demanding information on different machine learning and …
Insights into the recent advances of agro-industrial waste valorization for sustainable biogas production
Recent years have seen a transition to a sustainable circular economy model that uses agro-
industrial waste biomass waste to produce energy while reducing trash and greenhouse gas …
industrial waste biomass waste to produce energy while reducing trash and greenhouse gas …
Prediction of methyl orange dye (MO) adsorption using activated carbon with an artificial neural network optimization modeling
In this study, methyl orange (MO) dye removal by adsorption utilizing activated carbon made
from date seeds (DPAC) was modeled using an artificial neural network (ANN) technique …
from date seeds (DPAC) was modeled using an artificial neural network (ANN) technique …