Analysis and Forecasting of Geomagnetic Field Signal in Active Period
- https://doi.org/10.2991/icadme-15.2015.87How to use a DOI?
- geomagnetic variation field; active period; artificial neural network; modeling and forecasting.
Geomagnetic variation is divided into quiet period and active period, while active period is non-periodic and random. This paper utilizes analyze the magnetic variation field signals in active period in time-frequency domain, then models and forecasts the signals by using Artificial Neural Networks. The results show that the 4-hour-forecasting error of the three methods is . In multi-step forecasting, the method of GRNN is smooth, while LNN causes error increasing apparently. RBFNN has the best performance as its MAE is the smallest one for each time.
- © 2015, 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 - Dingxin Chen AU - Daizhi Liu AU - Liang Meng AU - Yihong Li AU - Chao Niu PY - 2015/10 DA - 2015/10 TI - Analysis and Forecasting of Geomagnetic Field Signal in Active Period BT - Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering PB - Atlantis Press SP - 433 EP - 437 SN - 2352-5401 UR - https://doi.org/10.2991/icadme-15.2015.87 DO - https://doi.org/10.2991/icadme-15.2015.87 ID - Chen2015/10 ER -