Graph Convolutional Neural Network for Pressure Prediction in Water Distribution Network Sites
Author:
Funder
National Natural Science Foundation of China
National Social Science Fund of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11269-024-03788-x.pdf
Reference23 articles.
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3. Galuppini G, Creaco EF, Magni L (2023) Multinode real-time control of pressure in water distribution networks via model predictive control. Trans Control Syst Technol, (pp 2201–2216). IEEE. https://doi.org/10.1109/TCST.2023.3291555
4. Giustolisi O, Kapelan Z, Savic D (2008) Algorithm for automatic detection of topological changes in water distribution networks. J Hydraul Eng 134(4):435–446
5. Glynis K, Kapelan Z, Bakker M, Taormina R (2023) Leveraging transfer learning in LSTM neural networks for data-efficient burst detection in water distribution systems. Water Resour Manage 37(15):5953–5972
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