Machine Learning for Solar Studies
- 作者: Illarionov E.A1,2, Sadykov V.M3
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隶属关系:
- Lomonosov Moscow State University
- Moscow Center for Fundamental and Applied Mathematics
- Georgia State University
- 期: 编号 4 (2021)
- 页面: 35-45
- 栏目: Articles
- URL: https://journals.eco-vector.com/0044-3948/article/view/630962
- DOI: https://doi.org/10.7868/S0044394821040034
- ID: 630962
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详细
In the paper we show several examples, when the machine learning algorithms help to solve the problems in solar studies and what are the main features of this approach. We discuss convolutional neural networks; cluster analysis; and binary classification.
作者简介
E. Illarionov
Lomonosov Moscow State University; Moscow Center for Fundamental and Applied MathematicsMoscow, Russia; Moscow, Russia
V. Sadykov
Georgia State UniversityAtlanta, GA, USA
参考
- Silver D. et al. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm, 2017, arxiv:1712.01815
- Витинский Ю.И. Солнечная активность. 2-е изд. М.: Наука, 1983.
- Camporeale E., Wing S., Johnson J. Machine Learning Techniques for Space Weather, 2018.
- Murphy K. Machine Learning: A Probabilistic Perspective, 2012. MIT Press, ISBN: 9780262018029
- Bishop C. Pattern Recognition and Machine Learning, 2006. Springer-Verlag New York. ISBN978-0-387-31073-2
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