From Deterministic to Probabilistic Forecasts of Water Demand-Reference-Cited by-同舟云学术

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From Deterministic to Probabilistic Forecasts of Water Demand

Published:2024-09-12 Issue: Volume:6 Page:122
ISSN:
Container-title:The 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI 2024)
language:
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Author:

Gabriele Annalaura¹^ORCID,Biondi Daniela²^ORCID,Gargano Rudy¹^ORCID,Todini Ezio³

Affiliation:

1. Dipartimento di Ingegneria Civile e Meccanica, University of Cassino and Southern Lazio, 03043 Cassino, Italy

2. Department of Informatics, Modelling, Electronics and System Engineering, University of Calabria, 87036 Rende, Italy

3. Italian Hydrological Society, 40127 Bologna, Italy

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/69/1/122/pdf

Reference7 articles.

1. A Model Conditional Processor to Assess Predictive Uncertainty in Flood Forecasting;Todini;Int. J. River Basin Manag.,2008

2. Aggarwal, C.C. (2018). Neural Networks and Deep Learning: A Textbook, Springer.

3. Anele, A.O., Hamam, Y., Abu-Mahfouz, A.M., and Todini, E. (2017). Overview, Comparative Assessment and Recommendations of Forecasting Models for Short-Term Water Demand Prediction. Water, 9.

4. Assessment of Predictive Uncertainty within the Framework of Water Demand Forecasting Using the Model Conditional Processor (MCP);Alvisi;Urban Water J.,2015

5. Anele, A.O., Todini, E., Hamam, Y., and Abu-Mahfouz, A.M. (2018). Predictive Uncertainty Estimation in Water Demand Forecasting Using the Model Conditional Processor. Water, 10.

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