Optimization and control strategies of aeration in WWTPs: A review

Y Gu, Y Li, F Yuan, Q Yang - Journal of Cleaner Production, 2023 - Elsevier
Over the recent decades, the escalating expenses associated with energy provision
alongside the implementation of rigorous ecological regulations have engendered a …

Integration of green energy and advanced energy-efficient technologies for municipal wastewater treatment plants

Z Guo, Y Sun, SY Pan, PC Chiang - International journal of environmental …, 2019 - mdpi.com
Wastewater treatment can consume a large amount of energy to meet discharge standards.
However, wastewater also contains resources which could be recovered for secondary uses …

Parameter-varying artificial potential field control of virtual coupling system with nonlinear dynamics

Y Cao, J Wen, A Hobiny, P Li, T Wen - Fractals, 2022 - World Scientific
In rail transit systems, improving transportation efficiency has become a research hotspot. In
recent years, a new method of train control system based on virtual coupling has attracted …

[HTML][HTML] Energy consumption prediction in water treatment plants using deep learning with data augmentation

F Harrou, A Dairi, A Dorbane, Y Sun - Results in Engineering, 2023 - Elsevier
Wastewater treatment plants (WWTPs) are energy-intensive facilities that play a critical role
in meeting stringent effluent quality regulations. Accurate prediction of energy consumption …

Unlocking the potential of wastewater treatment: Machine learning based energy consumption prediction

Y Alali, F Harrou, Y Sun - Water, 2023 - mdpi.com
Wastewater treatment plants (WWTPs) are energy-intensive facilities that fulfill stringent
effluent quality norms. Energy consumption prediction in WWTPs is crucial for cost savings …

Adaptive critic control design with knowledge transfer for wastewater treatment applications

D Wang, X Li, M Zhao, J Qiao - IEEE Transactions on industrial …, 2023 - ieeexplore.ieee.org
The wastewater treatment process (WWTP) is of great significance to environmental
protection. To improve the efficiency of the WWTP, it is crucial to ensure that the dissolved …

A synthetic minority oversampling technique based on Gaussian mixture model filtering for imbalanced data classification

Z Xu, D Shen, Y Kou, T Nie - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Data imbalance is a common phenomenon in machine learning. In the imbalanced data
classification, minority samples are far less than majority samples, which makes it difficult for …

Energy consumption prediction using machine learning; a review

A Mosavi, A Bahmani - 2019 - preprints.org
Abstract Machine learning (ML) methods has recently contributed very well in the
advancement of the prediction models used for energy consumption. Such models highly …

A self-organizing fuzzy neural network modeling approach using an adaptive quantum particle swarm optimization

H Zhou, Y Li, H Xu, Y Su, L Chen - Applied Intelligence, 2023 - Springer
To enhance the model's flexibility, this study proposes a self-organizing fuzzy neural network
(SOFNN) modeling methodology based on an adaptive quantum particle swarm …

Multiobjective optimal control for wastewater treatment process using adaptive MOEA/D

H Zhou, J Qiao - Applied Intelligence, 2019 - Springer
Through the analysis of the biological wastewater treatment process (WWTP), a
multiobjective optimal control strategy is developed with the usage of energy consumption …