Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: a comprehensive review and future perspective
The application of artificial neural networks (ANNs) in the treatment of wastewater has
achieved increasing attention, as it enhances the efficiency and sustainability of wastewater …
achieved increasing attention, as it enhances the efficiency and sustainability of wastewater …
A novel long short-term memory artificial neural network (LSTM)-based soft-sensor to monitor and forecast wastewater treatment performance
Commercial instrumentation for measurement of various wastewater treatment processes
parameters is costly and time-consuming in wastewater treatment plants (WWTPs). Long …
parameters is costly and time-consuming in wastewater treatment plants (WWTPs). Long …
Physics-informed recurrent neural networks and hyper-parameter optimization for dynamic process systems
Many of the processes in chemical engineering applications are of dynamic nature.
Mechanistic modeling of these processes is challenging due to the complexity and …
Mechanistic modeling of these processes is challenging due to the complexity and …
Prediction of wastewater treatment quality using LSTM neural network
Wastewater treatment (WWT) process is used to prevent pollution of water sources,
improves sanitation condition, and reuse the water (mostly for agricultural purposes). One of …
improves sanitation condition, and reuse the water (mostly for agricultural purposes). One of …
LSTM-based wastewater treatment plants operation strategies for effluent quality improvement
Wastewater Treatment Plants (WWTPs) are facilities devoted to managing and reducing the
pollutant concentrations present in the urban residual waters. Some of them consist in …
pollutant concentrations present in the urban residual waters. Some of them consist in …
[HTML][HTML] Sliding window neural network based sensing of bacteria in wastewater treatment plants
Ensuring the performance of wastewater treatment processes is important to guarantee that
the final treated wastewater quality is safe for reuse. However, bacterial concentration …
the final treated wastewater quality is safe for reuse. However, bacterial concentration …
Cost effective soft sensing for wastewater treatment facilities
M Alvi, T French, R Cardell-Oliver, P Keymer… - Ieee …, 2022 - ieeexplore.ieee.org
Wastewater treatment plants are complex, non-linear, engineered systems of physical,
biological and chemical processes operating at different timescales. Sensor systems are …
biological and chemical processes operating at different timescales. Sensor systems are …
Using a supervised machine learning approach to predict water quality at the Gaza wastewater treatment plant
This paper presents the use of four machine learning algorithms including Gaussian process
regression (GPR), random forest (FR), extreme gradient boosting (XGB) and light gradient …
regression (GPR), random forest (FR), extreme gradient boosting (XGB) and light gradient …
Data-driven modelling based on artificial neural networks for predicting energy and effluent quality indices and wastewater treatment plant optimization
NB Mihaly, M Simon-Varhelyi, VM Cristea - Optimization and Engineering, 2022 - Springer
The present work aimed the Wastewater Treatment Plant (WWTP) optimization based on the
prediction of the WWTP energy and quality performance indices using Artificial Neural …
prediction of the WWTP energy and quality performance indices using Artificial Neural …
A hybrid modelling approach for reverse osmosis processes including fouling
D Gaublomme, W Quaghebeur, A Van Droogenbroeck… - Desalination, 2023 - Elsevier
A novel hybrid modelling approach, combining the strengths of a mechanistic reverse
osmosis (RO) model and a data-driven fouling model, is developed on a unique long-term …
osmosis (RO) model and a data-driven fouling model, is developed on a unique long-term …