Interpretable AI for Short-Term Water Demand Forecasting
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, Imperial College London, London SW7 2BU, UK
Publisher
MDPI
Link
https://www.mdpi.com/2673-4591/69/1/101/pdf
Reference8 articles.
1. Niknam, A., Zare, H.K., Hosseininasab, H., Mostafaeipour, A., and Herrera, M. (2022). A critical review of short-term water demand forecasting tools—What method should I use?. Sustainability, 14.
2. Short-term forecasting of household water demand in the UK using an interpretable machine learning approach;Xenochristou;J. Water Resour. Plan. Manag.,2021
3. (2024, January 12). Interpretable AI Documentation. Available online: https://docs.interpretable.ai/stable/.
4. (2024, March 26). Gurobi Optimizer Reference Manual. Available online: https://www.gurobi.com/documentation/current/refman/index.html.
5. From predictive methods to missing data imputation: An optimization approach;Bertsimas;J. Mach. Learn. Res.,2017
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