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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-11-01
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| Series: | International Journal of Disaster Risk Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13753-024-00592-4 |
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