## 1 Introduction  
Satellites provide an important societal infrastructure. They are used for many different applications, including broadcasting, communications, global navigation, positioning, meteorology, Earth observation, science, technology, security, and defense. Satellites are equipped with various sorts of electric devices and instruments for their various missions. However, the operation of satellite instruments is affected by space environmental conditions. High-energy electrons at geostationary orbit (GEO) levels can cause charging of the surfaces of cables and circuits in a spacecraft. Thus, high-energy electrons can penetrate deeply into circuits, and the penetration could lead to deep dielectric charging. For example, on 20 January 1994 an Intelsat K spacecraft at GEO lost altitude control owing to the failure of the momentum wheel control circuit. According to observations by Geostationary Operational Environmental Satellites (GOES), high-energy electron flux increased greatly during the Intelsat anomalies. Studies on the accident reported that these spacecraft anomalies occurred as a result of dielectric charging by high-intensity and long-duration enhancement of high-energy electrons [1,2]. These studies also reported that spacecraft anomalies at GEO are associated with the enhancement of high-energy electron flux. [PERSON] and [PERSON] [3] found that MeV electron flux at GEO is enhanced 1-2 days after the passage of a high-speed solar wind stream, [PERSON] and [PERSON] [4] refer to the variability in the electron flux resulting from geomagnetic storms, which in turn are usually triggered by intense coronal mass ejections (CMEs). Therefore, the enhancement of high-energy electron flux depends on and correlates with both coronal holes and CMEs. Therefore, the prediction of high-energy electron flux caused by these two events is a central challenge in space weather. The dynamics of high-energy electrons is still under investigation [5], though specialists in space physics have observed the enhancement. Many studies, however, have reported that the enhancement of high-energy electrons is correlated with high-speed solar wind [6,7]. High-energy electron flux is known to be controlled by the solar wind. Furthermore, the north-south component of the interplanetary magnetic field (IMF) is also known to be another important parameter promoting flux enhancement. Many prediction models for high-energy electron flux at GEO have been proposed. The motivation for developing predictors is to protect spacecraft from deep dielectric charging by providing vital information for operational teams. Methods based on statistical and neural network approaches have been proposed. A linear prediction filter has been developed using a statistical approach [8]. That model is capable of predicting the daily averages of electron flux at GEO. [PERSON] and [PERSON] have also investigated a predictor of the daily averaged flux at GEO using artificial neural networks [9]. Predictors based on neural network techniques have been developed for high-energy electron flux 24 h ahead [6,10-12]. We propose a novel forecasting system for high-energy electron flux (\(>\)2 MeV) at GEO using multiple sensors located at different positions. In a previous study [13], the forecast model incorporates four sensors from two satellites that observe solar wind parameters and high-energy electron flux. This paper extends the model to include multiple sensors monitoring the same kinds of states observed from multiple satellites at different positions. The relations between sensors are estimated using a supportvector machine (SVM) [14] for machine learning. We demonstrate the predictions for typical examples, a coronal hole and coronal mass ejections (CMEs). This paper investigates whether our proposed model is applicable to space forecasting, proposing a system composed of multiple sensors with multiple satellites.