Model Generalization in Arrival Runway Occupancy Time Prediction by Feature Equivalences. (arXiv:2201.11654v1 [cs.LG])

General real-time runway occupancy time prediction modelling for multiple
airports is a current research gap. An attempt to generalize a real-time
prediction model for Arrival Runway Occupancy Time (AROT) is presented in this
paper by substituting categorical features by their numerical equivalences.
Three days of data, collected from Saab Sensis' Aerobahn system at three US
airports, has been used for this work. Three tree-based machine learning
algorithms: Decision Tree, Random Forest and Gradient Boosting are used to
assess the generalizability …

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