A review of artificial intelligence in water purification and wastewater treatment: Recent advancements
Artificial intelligence (AI) is an emerging powerful novel technology that can model real-time
problems involving numerous intricacies. The modeling capabilities of AI techniques are …
problems involving numerous intricacies. The modeling capabilities of AI techniques are …
A review on state-of-the-art applications of data-driven methods in desalination systems
The substitution of conventional mathematical models with fast and accurate modeling tools
can result in the further development of desalination technologies and tackling the need for …
can result in the further development of desalination technologies and tackling the need for …
Investigation of the factors affecting reverse osmosis membrane performance using machine-learning techniques
Several factors affecting the RO membrane performance can be investigated mainly in two
groups; feed characteristics and operational parameters. In this work, the effect of feed …
groups; feed characteristics and operational parameters. In this work, the effect of feed …
Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration
Mathematical models have been developed to obtain a better understanding of membrane
fouling mechanisms. However, those models could not simulate the membrane fouling …
fouling mechanisms. However, those models could not simulate the membrane fouling …
Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor
With the increase in electricity supply from clean energy sources, electrochemical reduction
of carbon dioxide (CO 2) has received increasing attention as an alternative source of …
of carbon dioxide (CO 2) has received increasing attention as an alternative source of …
[HTML][HTML] Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal
Abstract Machine learning models were developed for the intermittent multi-mode operation
of a wellhead reverse osmosis water purification and desalination system to predict salt …
of a wellhead reverse osmosis water purification and desalination system to predict salt …
Dead-end and crossflow ultrafiltration process modelling: Application on chemical mechanical polishing wastewaters
K Ohanessian, M Monnot, P Moulin, JH Ferrasse… - … Research and Design, 2020 - Elsevier
Dynamic simulation of ultrafiltration process is applied to the treatment of chemical
mechanical polishing wastewater from microelectronic industry. The ultrafiltration of …
mechanical polishing wastewater from microelectronic industry. The ultrafiltration of …
Surface and sub-surface flow estimation at high temporal resolution using deep neural networks
Recent intensification in climate change have resulted in the rise of hydrological extreme
events. This demands modeling of hydrological processes at high temporal resolution to …
events. This demands modeling of hydrological processes at high temporal resolution to …
Data driven identification of industrial reverse osmosis membrane process
P Dologlu, H Sildir - Computers & Chemical Engineering, 2022 - Elsevier
A dynamic artificial neural network (ANN) is developed for the identification of an industrial
reverse osmosis membrane process under fouling effect. 4-year historical data on feed …
reverse osmosis membrane process under fouling effect. 4-year historical data on feed …
Prediction of reverse osmosis membrane fouling in water reuse by integrated adsorption and data-driven models
Y Teng, HY Ng - Desalination, 2024 - Elsevier
In contemporary society, the reverse osmosis (RO) process is important for water treatment
and reuse industry. However, membrane fouling remains a challenging issue during …
and reuse industry. However, membrane fouling remains a challenging issue during …