## 2 Data and Sensor System
### Profiling: Identifying Events and Their Characteristics
The SVM evaluates the relation between the two sensors based on the test data. The SVM outputs the binary values \(+1/\
eg 1\) for the target sensor as the diagnosis result. The output range of the SVM corresponds to values of the parameter Tij. Finally, this test process assigns \(+1\) or \(-1\) to the parameter Tij. Figure 5 shows plots of an appearance of a coronal hole from 21 August 2008. All the plots were created from 16 August 2008 at 00:00:00 UTC to 21 August 2008 at 23:00:00 UTC. High-speed solar wind is observed at the beginning of the data at STEREO-A. Subsequently, high-speed solar wind data also are observed by the two satellites of ACE and STEREO-B. The solar wind speed observed by ACE rapidly increases from 400 km/s to 600 km/s at the time 52 h from the start of the sensor data. Simultaneously, the north-south component of IMF observed by ACE and STEREO-A also changes rapidly when the high-speed solar wind is recorded. In the plot, the high-energy election flux observed by GOES-10 approaches a warning level at the time 80-120 h after the  
Figure 5: Time development of sensor data for five days from 16 August 2008 at 00:00:00 UTC. This plot contains an event of high-speed solar wind flowing from a coronal hole. In the first and second rows, the plots of the columns correspond to the satellites of ACE, STEREO-A, and STEREO-B, respectively. In the third row, the plot corresponds to GOES-10. component of IMF is observed by ACE. The crucial task for the proposed model is prediction of the warning level of the high-energy electron flux during 80-120 h in the plot. The observed data shown in Figure 5 are sent to sensor nodes in the dynamic relational network. Each node reads the sensor data at every step and evaluates the credibility of the target node based on the sign of the arc. The state of the network changes according to the time development of the sensor data. Figure 6 shows the time development of the credibility of each node for the network shown in Figure 1a. Each node keeps high credibility until the high-energy electron flux increases at the time 60 h from the start of the data. The network detects the enhancement of the high-energy electron flux. However, the credibility of each sensor is unstable. The high-energy electron flux 24 h ahead detects the increase of flux after 80 h from the start of the data. The credibility of the high-energy electron flux 24 h ahead is still unstable. The node of the high-energy electron flux outputs an ambiguous prediction result. The credibility for the high-energy electron flux oscillates dynamically. Other nodes also report ambiguous results by detecting a deviation in the usual observation data. Figure 7 shows snapshots of the network based on the four sensors from two satellites. At the initial step, all nodes are evaluated as normal (Figure 7a). The plus and minus symbols on arcs represent evaluation: normal or abnormal. The criterion for abnormal detection of sensors is determined by comparing with a credibility and warning threshold. The warning threshold is 0.5 in this paper. The sensor node can be colored red if the credibility of the sensors exceeds the threshold. The symbols on arcs change if the sensor data deviates from the predefined conditions. The rectangle indicates a satellite with which a sensor is equipped. Figure 7b shows a sensor status of each sensor in the network at step 84. The status of the sensors is decorated by color according to its credibility. The diagnosis result of the arcs also is shown whole the network. At this step, the two nodes of the high-energy electron flux are evaluated as abnormal. Furthermore, other nodes of the north-south component of IMF and the solar wind speed are also evaluated as abnormal. These nodes are colored red where the credibility is very small, about 0.2. Figure 6: Time development of credibility for the test data shown in Figure 4. The four-sensor model evaluates the test data. The value of a vertical axis represent a credibility corresponding to a sensor name indicated at the vertical axis.