In recent decades, nature-inspired optimization methods have played a critical role in
helping industrial plant designers to find superior solutions for process parameters …

Wastewater treatment plants (WWTPs) are complex systems that must maintain high levels
of performance to achieve adequate effluent quality to protect the environment and public …

In this paper, we implement sustainable soft computing via application of Artificial Neural
Networks (ANN) to predict the desalination plant output more accurately. The proposed ANN …

Uncertainty qualification of estimated biological variables of Tabriz wastewater treatment
plant (WWTP) in Iran, was conducted by artificial intelligence-based modeling. The pollution …

An accurate prediction of the performance of water treatment desalination plants could
directly improve the global socio-economic balance. In this regard, many researchers have …

The management of traditional wastewater treatment plants (WWTPs) mostly rely on human
experience, resulting in high cost and low efficiency under conservative operation mode …

Prediction of effluent water quality is important for the management of wastewater treatment
plants (WWTPs). However, the accuracy of effluent quality prediction is poor owing to a lack …

Large amounts of bauxite-liquid residue are generated during the production of aluminium,
which has detrimental effects on human and environmental health. Currently, the primary …

Water treatment plant managers have to control quality and quantity indicators to regenerate
water to be used in irrigation or other municipal services. The need to improve the …

In wastewater treatment plants (WWTPs), the stochastic nature of influent wastewater and
operational and weather conditions cause fluctuations in effluent quality. Data-driven …