Predicting Tropical Cyclone Extreme Rainfall in Guangxi, China: An Interpretable Machine Learning Framework Addressing Class Imbalance and Feature Optimization
ABSTRACT Accurate prediction of tropical cyclone‐induced extreme rainfall (TCER) is of utmost importance for disaster mitigation in coastal regions. However, it remains a formidable challenge due to the intricate interactions among multi‐scale meteorological factors and the inherent data imbalances....
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-05-01
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| Series: | Meteorological Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/met.70052 |
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