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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Xehetasun bibliografikoak
Egile Nagusiak: Jun Tang, Mingfei Ding, Dengpan Yang, Cihang Fan, Nasim Khonsari, Wenfei Mao
Formatua: Artikulua
Hizkuntza:English
Argitaratua: Elsevier 2024-06-01
Saila:International Journal of Applied Earth Observations and Geoinformation
Gaiak:
Ionospheric TEC
Prediction
Random forest
Autoformer
Deep learning
Sarrera elektronikoa:http://www.sciencedirect.com/science/article/pii/S1569843224002437

Internet

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

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