Deep Learning Model-Based Demand Forecasting for Secondary Water Supply in Residential Communities: A Case Study of Shanghai City, China

Deep Learning Model-Based Demand Forecasting for Secondary Water Supply in Residential Communities: A Case Study of Shanghai City, China

To promote intelligent water services and accelerate the water industry’s modernization process, accurately predicting regional residents’ water demand and reducing energy consumption for secondary water supply is a major challenge for scientific scheduling and efficient manage...

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Bibliographic Details
Main Authors: Dali Li, Qingwen Fu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Water demand prediction
outlier identification
LSTM model
transformer model
deep learning
Online Access:https://ieeexplore.ieee.org/document/10159385/

Internet

https://ieeexplore.ieee.org/document/10159385/

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