Risk Assessment of Bridge Damage Due to Heavy Rainfall Considering Landslide Risk and Driftwood Generation Potential Using Convolutional Neural Networks and Conventional Machine Learning
This study addresses the assessment of bridge damage risks associated with heavy rainfall, focusing on landslide susceptibility and driftwood generation potential. By integrating convolutional neural networks (CNNs) with traditional machine learning methods, the research develops an advanced predict...
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Veröffentlicht in: | Water (Basel) 2024-12, Vol.16 (23), p.3471 |
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Format: | Artikel |
Sprache: | eng |
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