Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks

Andres Tello*, Huy Truong*, Alexander Lazovik, Victoria Degeler. Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings. 2024; 69(1):50. https://doi.org/10.3390/engproc2024069050 (*) Both authors contributed equally. Update (04/09/2024): Citation is updated.We have added headers for CSVs and auxiliary data (duration time, edge list, ordered names.. ) in the configuration file (JSON format). As such, corresponding INP files can be omitted when working with this version. The EXN network has been included in this version, so the total number of processed networks is 11.For more details, please read ZENODO_README.md. Contact For dataset-related questions: Huy Truong For data acquisition: Andres Tello If you use this dataset, please cite: @article{tello2024largescale, AUTHOR = {Tello, Andrés and Truong, Huy and Lazovik, Alexander and Degeler, Victoria}, TITLE = {Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks}, JOURNAL = {Engineering Proceedings}, VOLUME = {69}, YEAR = {2024}, NUMBER = {1}, ARTICLE-NUMBER = {50}, URL = {https://www.mdpi.com/2673-4591/69/1/50}, ISSN = {2673-4591}, DOI = {10.3390/engproc2024069050}}