Assessing the Risk of Extreme Storm Surges from Tropical Cyclones under Climate Change Using Bidirectional Attention-Based LSTM for Improved Prediction

Accurate prediction of storm surges is crucial for mitigating the impact of extreme weather events. This paper introduces the Bidirectional Attention-based Long Short-Term Memory (LSTM) Storm Surge Architecture, BALSSA, addressing limitations in traditional physical models. By leveraging machine lea...

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Detalhes bibliográficos

Principais autores:	Vai-Kei Ian, Su-Kit Tang, Giovanni Pau
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-11-01
coleção:	Atmosphere
Assuntos:	storm surge coastal hazards machine learning artificial intelligence tropical cyclone climate change
Acesso em linha:	https://www.mdpi.com/2073-4433/14/12/1749
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