A framework for forecasting the hourly nodal water demand and improving the performance of real-time hydraulic models considering model uncertainty

A framework for forecasting the hourly nodal water demand and improving the performance of real-time hydraulic models considering model uncertainty

The real-time hydraulic model (RTHM) is a key assistive tool in water distribution system (WDS) management, and its performance directly affects assisted decision-making. This study develops a framework to improve the timeliness and accuracy of RTHMs, which includes the following five steps: flow da...

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Bibliografiska uppgifter
Huvudupphovsmän: Cai Jian, Jinliang Gao, Yongpeng Xu, Liqun Deng
Materialtyp: Artikel
Språk:English
Publicerad: IWA Publishing 2022-05-01
Serie:Journal of Hydroinformatics
Ämnen:
data assimilation
machine learning algorithms
model uncertainty analysis
real-time hydraulic model
real-time state estimation
water demand prediction models
Länkar:http://jh.iwaponline.com/content/24/3/497

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