Interpretable Machine Learning for Thermospheric Mass Density Modeling Using GRACE/GRACE‐FO Satellite Data

Abstract With rapid development of artificial intelligence technology, machine learning has been widely applied to the thermospheric mass density (TMD) modeling. In this study we propose a machine‐learning approach, the bidirectional gated recurrent unit with multi‐head attention mechanism (BGMA), f...

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Bibliographic Details
Main Authors: Qian Pan, Chao Xiong, ShunZu Gao, Zhou Chen, Artem Smirnov, Chunyu Xu, Yuyang Huang
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:Space Weather
Online Access:https://doi.org/10.1029/2024SW004259
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