A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network
AbstractThis paper proposes a space weather forecasting system at geostationary orbit for high-energy electron ﬂux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic ﬁeld and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron ﬂux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.
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Tokumitsu, M.; Ishida, Y. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network. Sensors 2014, 14, 7974-7991.
Tokumitsu M, Ishida Y. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network. Sensors. 2014; 14(5):7974-7991.Chicago/Turabian Style
Tokumitsu, Masahiro; Ishida, Yoshiteru. 2014. "A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network." Sensors 14, no. 5: 7974-7991.