In wastewater treatment process (WWTP), the accurate and real-time monitoring values of
key variables are crucial for the operational strategies. However, most of the existing …

The effluent total phosphorus (ETP) is an important parameter to evaluate the performance
of wastewater treatment process (WWTP). In this study, a novel method, using a data …

At present, wastewater treatment quality parameters cannot be detected on-line. In this
paper, the soft-sensing method based on artificial neural networks is proposed in order to …

Real‐time measurements of key effluent parameters play a highly crucial role in wastewater
treatment. In this research work, we propose a soft sensor model based on deep learning …

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 …

The nonlinearity and complicated biological phenomena existing in wastewater treatment
processes (WWTP) make the operation and modeling of WWTP quite difficult. In this study, a …

Ammonia-nitrogen concentration is a key water quality indicator, which reflects changes in
pollutant components during wastewater treatment processes. The timely and accurate …

Recent studies into the estimation and control of an activated sludge process (ASP) at a
wastewater treatment plant suggest that artificial-intelligence methods, such as neural …

Soft-sensor applications for wastewater management can provide valuable information for
intelligent monitoring and process control above and beyond what is available from …

Soft sensors are widely used to estimate process variables that are difficult to measure
online. However, due to poor quality of input data and deterioration of prediction model as …