Long short-term memory and gated recurrent neural networks to predict the ionospheric vertical total electron content-Reference-Cited by-同舟云学术

Long short-term memory and gated recurrent neural networks to predict the ionospheric vertical total electron content

Published:2022-08 Issue:3 Volume:70 Page:652-665
ISSN:0273-1177
Container-title:Advances in Space Research
language:en
Short-container-title:Advances in Space Research

Author:

Iluore Kenneth,Lu Jianyong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Space and Planetary Science,Aerospace Engineering,General Earth and Planetary Sciences,Atmospheric Science,Geophysics,Astronomy and Astrophysics

Reference55 articles.

1. Ionospheric foF2 variability over the southeast Asian sector. Journal of Geophysical Research: Space;Akala;Physics,2010

2. Bahdanau, D., Cho, K.H., Bengio, Y., 2015. Neural machine translation by jointly learning to align and translate. In: Paper presented at 3rd International Conference on Learning Representations, ICLR San Diego, United States.

3. TEC derived from GPS network in India and comparison with the IRI;Bhuyan;Adv. Space Res.,2007

4. Bilitza, D., 1990. International Reference Ionosphere. URSI/COSPAR Task Group on International Reference Ionosphere.

5. The Theory of Radio Waves of Low Power in the Ionosphere and Magnetosphere;Budden,1985

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