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Application of deep learning methods to predict ionosphere parameters in real time
- Source :
- E3S Web of Conferences, Vol 196, p 02007 (2020)
- Publication Year :
- 2020
- Publisher :
- EDP Sciences, 2020.
-
Abstract
- In this paper, the previously obtained results on recognition of ionograms using deep learning are expanded to predict the parameters of the ionosphere. After the ionospheric parameters have been identified on the ionogram using deep learning in real time, we can predict the parameters for some time ahead on the basis of the new data obtained Examples of predicting the ionosphere parameters using an artificial recurrent neural network architecture long short-term memory are given. The place of the block for predicting the parameters of the ionosphere in the system for analyzing ionospheric data using deep learning methods is shown.
- Subjects :
- Environmental sciences
GE1-350
Subjects
Details
- Language :
- English, French
- ISSN :
- 22671242
- Volume :
- 196
- Database :
- Directory of Open Access Journals
- Journal :
- E3S Web of Conferences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5c6b089d0cd4b7e9b88557a3052bef6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1051/e3sconf/202019602007