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

<p>&nbsp;</p> <div> <div><a href="https://arxiv.org/search/cs?searchtype=author&amp;query=Tello,+A">Andres Tello*</a><em>, </em><a href="https://arxiv.org/search/cs?searchtype=author&amp;query=Truong,+H">Huy Truong*</a>, <a href="https://arxiv.org/search/cs?searchtype=author&amp;query=Lazovik,+A">Alexander Lazovik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&amp;query=Degeler,+V">Victoria Degeler</a>. Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings. 2024; 69(1):50. <a href="https://doi.org/10.3390/engproc2024069050">https://doi.org/10.3390/engproc2024069050</a></div> <br> <div>(*) Both authors contributed equally.<br><br></div> <h2>Update</h2> <div>(04/09/2024): Citation is updated.<br>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.&nbsp;<br>The EXN network has been included in this version, so the total number of processed networks is 11.<br>For more details, please read ZENODO_README.md.</div> <h2>Contact</h2> <div>For dataset-related questions: <a href="mailto:h.c.truong@rug.nl" target="_blank" rel="noopener">Huy Truong</a></div> <br> <div>For data acquisition: <a href="mailto:a.tello@rug.nl" target="_blank" rel="noopener">Andres Tello</a></div> <br> <div>If you use this dataset, please cite:</div> <blockquote>@article{tello2024largescale,<br>&nbsp; &nbsp; AUTHOR = {Tello, Andr&eacute;s and Truong, Huy and Lazovik, Alexander and Degeler, Victoria},<br>&nbsp; &nbsp; TITLE = {Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks},<br>&nbsp; &nbsp; JOURNAL = {Engineering Proceedings},<br>&nbsp; &nbsp; VOLUME = {69},<br>&nbsp; &nbsp; YEAR = {2024},<br>&nbsp; &nbsp; NUMBER = {1},<br>&nbsp; &nbsp; ARTICLE-NUMBER = {50},<br>&nbsp; &nbsp; URL = {https://www.mdpi.com/2673-4591/69/1/50},<br>&nbsp; &nbsp; ISSN = {2673-4591},<br>&nbsp; &nbsp; DOI = {10.3390/engproc2024069050}<br>}</blockquote> </div>