A Novel Air Traffic Management and Control Methodology using Fault-Tolerant Autoencoder and P2P Blockchain Application on the UAS-S4 Ehécatl
Author:
Affiliation:
1. Ecole de technologie superieure
Publisher
American Institute of Aeronautics and Astronautics
Link
https://arc.aiaa.org/doi/pdf/10.2514/6.2023-2190
Reference48 articles.
1. On controller synthesis for nonlinear hybrid systems
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3. Commercial Aircraft Lateral Flight Reference Trajectory Optimization
4. Path Planning for Autonomous Underwater Vehicles
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1. Bidirectional Long Short-Term Memory Development for Aircraft Trajectory Prediction Applications to the UAS-S4 Ehécatl;Aerospace;2024-07-31
2. Fault-tolerant Trajectory Prediction Using Random Forest Methodology Application to UAS-S4 Ehécatl;AIAA SCITECH 2024 Forum;2024-01-04
3. Robust Trajectory Prediction Using Random Forest Methodology Application to UAS-S4 Ehécatl;Aerospace;2024-01-02
4. A Blockchain-Powered Traffic Management System for Unmanned Aerial Vehicles;Applied Sciences;2023-10-04
5. Aircraft Trajectory Prediction Enhanced through Resilient Generative Adversarial Networks Secured by Blockchain: Application to UAS-S4 Ehécatl;Applied Sciences;2023-08-22
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