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Urban Water Journal Volume 17, 2020 - Issue 3
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Research Articles

An ensemble stacked model with bias correction for improved water demand forecasting

Maria Xenochristoua Centre for Water Systems, University of Exeter, Exeter, UKCorrespondence[email protected]
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Zoran Kapelana Centre for Water Systems, University of Exeter, Exeter, UK;b Department of Water Management., Delft University of Technology, Delft, NetherlandsView further author information
Pages 212-223 | Received 07 Sep 2019, Accepted 06 Apr 2020, Published online: 13 May 2020

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Sarai Díaz & Javier González. (2022) Short‐Term Variability Effect on Peak Demand: Assessment Based on a Microcomponent Stochastic Demand Model. Water Resources Research 58:1.
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Emilio Ruiz, Sarai Díaz & Javier González. (2022) Potential Performance of Hydraulic State Estimation in Water Distribution Networks. Water Resources Management 36:2, pages 745-762.
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Dong-Gi Lee & Kuk-Hyun Ahn. (2021) A stacking ensemble model for hydrological post-processing to improve streamflow forecasts at medium-range timescales over South Korea. Journal of Hydrology 600, pages 126681.
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Kang-Min Koo, Kuk-Heon Han, Kyung-Soo Jun, Gyumin Lee, Jung-Sik Kim & Kyung-Taek Yum. (2021) Performance Assessment for Short-Term Water Demand Forecasting Models on Distinctive Water Uses in Korea. Sustainability 13:11, pages 6056.
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Andrea Menapace, Ariele Zanfei & Maurizio Righetti. (2021) Tuning ANN Hyperparameters for Forecasting Drinking Water Demand. Applied Sciences 11:9, pages 4290.
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Maria Xenochristou, Chris HuttonJan Hofman & Zoran Kapelan. (2021) Short-Term Forecasting of Household Water Demand in the UK Using an Interpretable Machine Learning Approach. Journal of Water Resources Planning and Management 147:4.
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Omid Hamidi, Hamed Abbasi & Hamid Mirhashemi. (2021) Analysis of the Response of Urban Water Consumption to Climatic Variables: Case Study of Khorramabad City in Iran. Advances in Meteorology 2021, pages 1-14.
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Diana Fiorillo, Zoran Kapelan, Maria Xenochristou, Francesco De Paola & Maurizio Giugni. (2021) Assessing the Impact of Climate Change on Future Water Demand using Weather Data. Water Resources Management 35:5, pages 1449-1462.
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M. Xenochristou, C. Hutton, J. Hofman & Z. Kapelan. (2020) Water Demand Forecasting Accuracy and Influencing Factors at Different Spatial Scales Using a Gradient Boosting Machine. Water Resources Research 56:8.
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