Urban Water Consumption Prediction Based on CPMBNIP
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03601-1.pdf
Reference54 articles.
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3. Ashu AB, Lee SI (2021) The effects of climate change on the reuse of agricultural drainage water in irrigation. KSCE J Civ Eng 25(3):1116–1129. https://doi.org/10.1007/s12205-021-0004-2
4. Bai Y, Wang P, Li C, Xie JJ, Wang Y (2014) A multi-scale relevance vector regression approach for daily urban water demand forecasting. J Hydrol 517:236–245. https://doi.org/10.1016/j.jhydrol.2014.05.033
5. Bata MH, Carriveau R, Ting DSK (2020) Short-term water demand forecasting using nonlinear autoregressive artificial neural networks. J Water Resour Plan Manag 146(3):04020008. https://doi.org/10.1061/(asce)wr.1943-5452.0001165
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