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

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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Bibliographic Details
Main Authors: Vai-Kei Ian, Su-Kit Tang, Giovanni Pau
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Atmosphere
Subjects:
storm surge
coastal hazards
machine learning
artificial intelligence
tropical cyclone
climate change
Online Access:https://www.mdpi.com/2073-4433/14/12/1749

Internet

https://www.mdpi.com/2073-4433/14/12/1749

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