A pipeline of XGBoost sector prediction, leaderless Paxos coordination, and per-airport Bayesian optimization achieves 91% prediction accuracy and over 96% entry success in FAA-derived simulations for scalable autonomous airspace management.
Predictive sectorization and Bayesian optimized consen- sus for admission control in autonomous airspace operations
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Predictive Sectorization and Bayesian Optimized Consensus for Admission Control in Autonomous Airspace Operations
A pipeline of XGBoost sector prediction, leaderless Paxos coordination, and per-airport Bayesian optimization achieves 91% prediction accuracy and over 96% entry success in FAA-derived simulations for scalable autonomous airspace management.