Andrés Tello & Huy Truong presented the paper: "Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks" at the WDSA/CCWI 2024 Conference.

This work was presented at the 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI), held in Ferrara, Italy, from July 01st – 04th.

Andrés & Huy contributed with a dataset that includes 10 Water Distribution Networks at different locations around the world. The dataset provides over 1.3 million WDN stable states, eliminating the need for re-simulation. An automatic demand generation mitigates the overuse of temporal patterns, enhancing the variability of data. The publicly available dataset serves as a benchmark for comparing models across different tasks.