Investigation of the impact of token embeddings in Transformer-based models on short-term tropical cyclone track and intensity predictions

Investigation of the impact of token embeddings in Transformer-based models on short-term tropical cyclone track and intensity predictions

Tropical cyclones (TCs) are destructive meteorological phenomena, necessitating accurate predictions of TC track and intensity to reduce risks to human life. This study evaluates three Transformer-based models – vanilla Transformer (Transformer), inverted Transformer (iTransformer), and temporal-var...

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Bibliographic Details
Main Authors: Yuan-Jiang Zeng, Yi-Qing Ni, Zheng-Wei Chen, Guang-Zhi Zeng, Jia-Yao Wang, Pak-Wai Chan
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Tropical cyclones
track
intensity
Transformer
token embeddings
Online Access:https://www.tandfonline.com/doi/10.1080/19942060.2025.2538180
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https://www.tandfonline.com/doi/10.1080/19942060.2025.2538180

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