Solar Wind Speed Prediction via Graph Attention Network

Author:

Sun Yanru1,Xie Zongxia1ORCID,Wang Haocheng1,Huang Xin2,Hu Qinghua1ORCID

Affiliation:

1. College of Intelligence and Computing Tianjin University Tianjin China

2. National Astronomical Observatories Chinese Academy of Sciences Beijing China

Funder

National Science and Technology Major Project

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

Reference39 articles.

1. Improvement in the prediction of solar wind conditions using near-real time solar magnetic field updates

2. Bai S. Kolter J. Z. &Koltun V.(2018).An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271.

3. Cho K. Van Merriënboer B. Gulcehre C. Bahdanau D. Bougares F. Schwenk H. &Bengio Y.(2014).Learning phrase representations using rnn encoder‐decoder for statistical machine translation. arXiv preprint arXiv:1406.1078.

4. Convolutional neural networks on graphs with fast localized spectral filtering;Defferrard M.;Advances in Neural Information Processing Systems,2016

5. A hybrid heliospheric modeling system: Background solar wind

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