Leak Localization Using Autoencoders and Shapley Values
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, The Norwegian University of Science and Technology (NTNU), 7031 Trondheim, Norway
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/69/1/92/pdf
Reference8 articles.
1. (2024, January 15). Statistics Norway. Available online: https://www.ssb.no/en/natur-og-miljo/vann-og-avlop/statistikk/kommunal-vannforsyning.
2. Health risks due to intrusion into the drinking water distribution network: Hydraulic modelling and quantitative microbial risk assessment;Odhiambo;Environ. Sci. Water Res. Technol.,2023
3. Review of model-based and data-driven approaches for leak detection and location in water distribution systems;Hu;Water Supply.,2021
4. Benefits and challenges of using smart meters for advancing residential water demand modeling and management: A review;Cominola;Environ. Model. Softw.,2015
5. Baldi, P. (2011, January 2). Autoencoders, Unsupervised Learning, and Deep Architectures. Proceedings of the ICML Workshop on Unsupervised and Transfer Learning, Washington, DC, USA.
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