Modelling wastewater processes supports tasks such as process prediction, soft sensing,
data analysis and computer assisted design of wastewater systems. Wastewater treatment …

Artificial neural networks (ANNs) have recently attracted significant attention in
environmental areas because of their great self-learning capability and good accuracy in …

The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …

In this study, a combined alkaline (ALK) and ultrasonication (ULS) sludge lysis-cryptic
pretreatment and anoxic/oxic (AO) system (AO+ ALK/ULS) was developed to enhance …

Accurate simulation of wastewater effluent parameters is a vital concern to reduce the
operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a …

Improving the operation, management, and consequent performance of wastewater
treatment plants (WWTPs) for conserving the water environment is crucial. Recent …

Artificial intelligence is finding its ways into the mainstream of day-to-day operations. Novel
AI application techniques such as the artificial neural network (ANN), fuzzy logic, genetic …

Water quality has a crucial impact on human health; therefore, water quality index modeling
is one of the challenging issues in the water sector. The accurate prediction of water quality …

Artificial neural networks (ANNs) have achieved great success in performing machine
learning tasks, including classification, regression, prediction, image processing, image …

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) magnetic
nanocomposites were prepared and then applied in the Cu (II) removal from aqueous …