A Deep U-Net-ConvLSTM Framework with Hydrodynamic Model for Basin-Scale Hydrodynamic Prediction

A Deep U-Net-ConvLSTM Framework with Hydrodynamic Model for Basin-Scale Hydrodynamic Prediction

Traditional hydrodynamic models face the significant challenge of balancing the demands of long prediction spans and precise boundary conditions, large computational areas, and low computational costs when attempting to rapidly and accurately predict the nonlinear spatial and temporal characteristic...

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Bibliographic Details
Main Authors: Ao Li, Wanshun Zhang, Xiao Zhang, Gang Chen, Xin Liu, Anna Jiang, Feng Zhou, Hong Peng
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Water
Subjects:
deep learning
U-Net
ConvLSTM
hydrodynamic prediction
Online Access:https://www.mdpi.com/2073-4441/16/5/625

Internet

https://www.mdpi.com/2073-4441/16/5/625

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