Numerical weather prediction data during a time period of interest for a multi-airport system is used to generate a three-dimensional (3-D) tensor data for the time period of interest. The 3-D tensor data is then used to predict hourly runway configurations for each of a plurality of airports of the multi-airport system during the time period of interest using the 3-D tensor data as input to a plurality of runway configuration convolutional neural networks (CNN) branches and to predict an AAR for each of the plurality of airports of the multi-airport system during the time period of interest using the 3-D tensor data as input to an airport acceptance rate (AAR) CNN branch. The predicted hourly runway configuration for each of the plurality of airports and the predicted AAR for each of the plurality of airports are then used to manage flights within the multi-airport system.
System and method for the prediction of runway configuration and airport acceptance rate (AAR) for multi-airport system
29.04.2025
Patent
Elektronische Ressource
Englisch
Probabilistic Airport Acceptance Rate Prediction
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