Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
TailBooster: A Dual-Layer Generative Framework for Extreme Value Augmentation with Operational Validity Enforcement
Karim Aly, Alexei Sharpanskykh, Jacco Hoekstra
Extreme events in air transport, such as severe arrival delays and abnormal air times, cause cascading network disruptions with substantial operational, economic, and safety costs.…
cs.LG2026
Synthetic Flight Data Generation Using Generative Models
Karim Aly, Alexei Sharpanskykh
The increasing adoption of synthetic data in aviation research offers a promising solution to data scarcity and confidentiality challenges. This study investigates the potential of…
cs.LG2026
Generative Augmentation of Imbalanced Flight Records for Flight Diversion Prediction: A Multi-objective Optimisation Framework
Karim Aly, Alexei Sharpanskykh, Jacco Hoekstra
Flight diversions are rare but high-impact events in aviation, making their reliable prediction vital for both safety and operational efficiency. However, their scarcity in histori…