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

机译:基于自识别网络的多卫星空间天气预报系统

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摘要

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.
机译:针对高能电子通量(> 2 MeV),本文提出了对地静止轨道的空间天气预报系统。预测模型涉及多个卫星上的多个传感器。传感器相互连接并相互评估,以预测地球静止轨道的未来状况。提出的预测模型是使用动态关系网络构建的,用于传感器诊断和事件监视。所提出的模型的传感器位于空间中的不同位置。用于太阳监测的卫星配有行星际磁场和太阳风速监测装置。卫星在地球附近运行,监视高能电子通量。我们通过比较具有不同数量传感器的两个模型的性能来调查典型两个示例的预测。我们证明了所提出的模型对冠状物质抛射和冠状孔的预测。本文旨在研究基于卫星网络的原位遥感空间天气预报的可能性。

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