Water demand forecasting in multiple district metered areas based on a multi-scale correction module neural network architecture

Water demand forecasting in multiple district metered areas based on a multi-scale correction module neural network architecture

Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand com...

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Bibliographic Details
Main Authors: Qidong Que, Jinliang Gao, Yizhou Qian
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Water Research X
Subjects:
Short-term water demand forecasting
Convolutional Neural Network
Attention mechanism
Long-short term memory neural network
Interpretability in deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2589914724000598
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