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HAPS-UAV-Enabled Heterogeneous Networks: A Deep Reinforcement Learning Approach
The integrated use of non-terrestrial network (NTN) entities such as the high-altitude platform station (HAPS) and low-altitude platform station (LAPS) has become essential elements in the space-air-ground integrated networks (SAGINs).
Satellite Anomaly Detection Using Variance Based Genetic Ensemble of Neural Networks
Then these uncertainty levels and each predictive model suggested by GA are used to generate a new model, which is then used for forecasting the TS and AD.
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout
In this paper, we present a tractable approximation for BNN based on the Monte Carlo (MC) dropout method for capturing the uncertainty in the satellite telemetry time series, without sacrificing accuracy.
UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms
However, due to UAVs' high dynamics and complexity, the real-world deployment of a SAGIN becomes a major barrier for realizing such SAGINs.
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