Prediction of Global Ionospheric TEC Based on Deep Learning-Reference-Cited by-同舟云学术

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Prediction of Global Ionospheric TEC Based on Deep Learning

Published:2022-04 Issue:4 Volume:20 Page:
ISSN:1542-7390
Container-title:Space Weather
language:en
Short-container-title:Space Weather

Author:

Chen Zhou¹²^ORCID,Liao Wenti¹²,Li Haimeng¹²^ORCID,Wang Jinsong³,Deng Xiaohua¹²,Hong Sheng²

Affiliation:

1. Institute of Space Science and Technology Nanchang University Nanchang China

2. Information Engineering School Nanchang University Nanchang China

3. Key Laboratory of Space Weather National Center for Space Weather Meteorological Administration Beijing China

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021SW002854

Reference20 articles.

1. IRI the International Standard for the Ionosphere

2. Improvement of a Deep Learning Algorithm for Total Electron Content Maps: Image Completion

3. Extraction of the geomagnetic activity effect from TEC data: A comparison between the spectral whitening method and 28 day running median

4. A global response of the total electron content of the ionosphere to the magnetic storm of 17 and 18 June 1972

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