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Sensors 2014, 14(5), 7974-7991;

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

Department of Electrical and Control Engineering, Yonago National College of Technology, Hikonacho 4448, Yonago, Tottori 683-0854, Japan
Department of Computer Science and Engineering, Toyohashi University of Technology/1-1, Tempaku, Toyohashi, Aichi 441-8580, Japan
Author to whom correspondence should be addressed.
Received: 9 December 2013 / Revised: 20 April 2014 / Accepted: 21 April 2014 / Published: 5 May 2014
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Japan 2012)
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This 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. View Full-Text
Keywords: self-recognizing network; sensor networks; space weather; in-situ sensing self-recognizing network; sensor networks; space weather; in-situ sensing
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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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.

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