A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes

A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes

Abstract Deep learning models demonstrate impressive performance in rapidly predicting urban floods, but there are still limitations in enhancing physical connectivity and interpretability. This study proposed an innovative modeling approach that integrates convolutional neural networks with weighte...

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Bibliographic Details
Main Authors: Jiarui Yang, Kai Liu, Ming Wang, Gang Zhao, Wei Wu, Qingrui Yue
Format: Article
Language:English
Published: SpringerOpen 2024-11-01
Series:International Journal of Disaster Risk Science
Subjects:
Convolutional neural networks
Physical continuity
Rapid prediction
Urban pluvial flooding processes
Weighted cellular automata
Online Access:https://doi.org/10.1007/s13753-024-00592-4
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https://doi.org/10.1007/s13753-024-00592-4

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