09 - Crewed and Uncrewed Aircraft Operations and Traffic Management
AIRCRAFT CLIMB PROFILE PREDICTION VIA MACHINE LEARNING-BASED FRAMEWORK
H. Seon¹, K. Lee¹, M. Brown², H. Hirabayashi²; ¹Korea Aerospace University, South Korea ;²Electronic Navigation Research Institute, Japan
To address climb rate mispredictions in fixed performance tables, this study investigates various machine learning models including Transformer. We analyze feature significance to understand how environmental and aircraft-specific factors contribute to prediction performance. The results demonstrate that data-driven approaches can significantly improve prediction accuracy over fixed-table method.
DOI: 10.71945/icas2026_0893