Reconstructing nodal pressures in water distribution systems with graph neural networks

1 code implementation • 28 Apr 2021 • Gergely Hajgató, Bálint Gyires-Tóth, György Paál

The reconstruction method is based on K-localized spectral graph filters, wherewith graph convolution on water networks is possible.

Friction

Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems

1 code implementation • 13 Oct 2020 • Gergely Hajgató, György Paál, Bálint Gyires-Tóth

The main contribution of the presented approach is that the agent can run the pumps in real-time because it depends only on measurement data.

reinforcement-learning Reinforcement Learning (RL)

Predicting the flow field in a U-bend with deep neural networks

no code implementations • 1 Oct 2020 • Gergely Hajgató, Bálint Gyires-Tóth, György Paál

This database was used to train an encoder-decoder style deep convolutional neural network to predict the velocity distribution from the geometry.