Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)

HF Frequency Short-Term Forecast Method Research in the Asia Oceania Region

Authors
Chao Li, Hanguang Jia, Huibin Hu, Yunjiang Liu, Xiangyang Ye
Corresponding Author
Chao Li
Available Online August 2018.
DOI
10.2991/icitme-18.2018.40How to use a DOI?
Keywords
autocorrelation coefficient; artificial neural network; foF2
Abstract

With analysis on ionosphere propagation features, and on the basis of ionospheric data in Sanya, Hainan, the self-correlation coefficient analysis method is applied to the ionospheric parameter prediction, then the method is compared with the artificial neural network prediction method. The prediction of the autocorrelation coefficients method is more close to the actual value, and more accurate scientific basis is provided for the HF frequency prediction.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)
Series
Advances in Intelligent Systems Research
Publication Date
August 2018
ISBN
10.2991/icitme-18.2018.40
ISSN
1951-6851
DOI
10.2991/icitme-18.2018.40How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chao Li
AU  - Hanguang Jia
AU  - Huibin Hu
AU  - Yunjiang Liu
AU  - Xiangyang Ye
PY  - 2018/08
DA  - 2018/08
TI  - HF Frequency Short-Term Forecast Method Research in the Asia Oceania Region
BT  - Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)
PB  - Atlantis Press
SP  - 201
EP  - 203
SN  - 1951-6851
UR  - https://doi.org/10.2991/icitme-18.2018.40
DO  - 10.2991/icitme-18.2018.40
ID  - Li2018/08
ER  -