Urban Water Supply Forecasting Based on CNN-LSTM-AM Spatiotemporal Deep Learning Model

Urban Water Supply Forecasting Based on CNN-LSTM-AM Spatiotemporal Deep Learning Model

Accurate and efficient forecasting of urban water supply is of great significance for urban water supply management. In this paper, a spatiotemporal deep learning model that integrates convolutional neural network (CNN), long short-term memory (LSTM), and attention mechanism (AM) is proposed for pre...

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Bibliographic Details
Main Authors: Yaxin Zhao, Yuebing Xu, Jiadong Ye, Xiaowu Zhang, Zuqiang Long
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Attention mechanism
Bayesian optimization
convolutional neural network
long short-term memory network
urban water supply forecasting
Online Access:https://ieeexplore.ieee.org/document/10366225/

Internet

https://ieeexplore.ieee.org/document/10366225/

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