Table 1.
Global contributions to SEE studies in nanosatellites.
Fig 1.
Structural analysis of nanosatellite.
Fig 2.
Overview of how nano-satellite system works.
Fig 3.
Flowchart of our proposed SEEnet.
Fig 4.
Decision tree flowchart for SEE_label prediction based on satellite telemetry parameters.
Fig 5.
Device level SEE propagation methodology.
Table 2.
Evaluating the performance of our algorithms with different models.
Fig 6.
Comparison of our algorithm via various ML models.
Fig 7.
Confusion Matrix of different ML models.
Fig 8.
Heatmap representation of SEEnet prediction outcomes on the test dataset.
Fig 9.
Geo-spatial distribution of SEE events.
Fig 10.
3D plot Geo-spatial distribution of SEE events.
Fig 11.
Kernel Density Estimate (KDE) plot.
Fig 12.
Hexbin plot.
Fig 13.
Correlation matrix between different parameters.
Fig 14.
Time-series plot over a period of time.
Table 3.
Comparison of SEEnet with existing SEE prediction models.