Different data-driven prediction of global ionospheric TEC using deep learning methods

Different data-driven prediction of global ionospheric TEC using deep learning methods

Ionospheric Total Electron Content (TEC) is a crucial parameter for monitoring the ionosphere and space weather disasters. Its accurate prediction is vital for precise applications of Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS). This study proposes...

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Detalles Bibliográficos
Autores principales: Jun Tang, Mingfei Ding, Dengpan Yang, Cihang Fan, Nasim Khonsari, Wenfei Mao
Formato: Artículo
Lenguaje:English
Publicado: Elsevier 2024-06-01
Colección:International Journal of Applied Earth Observations and Geoinformation
Materias:
Ionospheric TEC
Prediction
Random forest
Autoformer
Deep learning
Acceso en línea:http://www.sciencedirect.com/science/article/pii/S1569843224002437

Internet

http://www.sciencedirect.com/science/article/pii/S1569843224002437

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