In wastewater monitoring, detecting extremely high pollutant concentrations is necessary to
properly calibrate the treatment process. However, existing hardware sensors have a limited …

To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …

At this time, efforts are being made on a worldwide scale to accomplish sustainable
development objectives. It has, thus, now become essential to investigate the part of …

This study focuses on the simultaneous degradation (co-degradation) of two organic
pollutants; one of them is a textile dye (solophenyl brown AGL), while the other is a …

Wastewater is created by pharma firms and has become a huge worry for the ecosystem. ere
is a significant amount of toxins that are being dropped continuously from numerous …

It is a difficult task to select one proxy model with the proper range of accuracy and speed
among various models. In the current study various types of sampling and surrogate models …

Sludge bulking is a major problem in activated sludge processes. It is of great practically
useful to predict the sludge settleability through water quality (influent and effluent) and the …

The treatment of wastewater is a complicated biological reaction process. Reliable effluent
prediction is critical in the scientific management of water treatment plants. This research …

Increasing water demand for utilization in various sectors throughout the world poses rapid
technological interventions in recycling and reuse of wastewater for ensuring environmental …

A predictive model based on artificial neural networks (ANNs) for modeling primary settling
tanks'(PSTs) behavior in wastewater treatment plants was developed in this study. Two …