Real-time flood maps forecasting for dam-break scenarios with a transformer-based deep learning model-Reference-Cited by-同舟云学术

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Real-time flood maps forecasting for dam-break scenarios with a transformer-based deep learning model

Published:2024-05 Issue: Volume:635 Page:131169
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Pianforini Matteo^ORCID,Dazzi Susanna^ORCID,Pilzer Andrea,Vacondio Renato^ORCID

Publisher

Elsevier BV

Reference41 articles.

1. Dam-Break Flows: Acquisition of Experimental Data through an Imaging Technique and 2D Numerical Modeling;Aureli;J. Hydraul. Eng.,2008

2. Deep learning methods for flood mapping: a review of existing applications and future research directions;Bentivoglio;Hydrol. Earth Syst. Sci.,2022

3. Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks;Bentivoglio;Hydrol. Earth Syst. Sci.,2023

4. A rapid flood inundation model for hazard mapping based on least squares support vector machine regression;Bermúdez;J. Flood Risk Manage.,2019

5. Is Space-Time Attention All You Need for Video Understanding?;Bertasius,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting Flood Inundation after a Dike Breach Using a Long Short-Term Memory (LSTM) Neural Network;Hydrology;2024-09-12

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