AeroSense directly models microscopic aircraft states with masked self-attention to predict heterogeneous air traffic flows, outperforming time series baselines on real airport data.
Irregular traffic time series forecasting based on asynchronous spatio-temporal graph convolutional networks
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From Time Series to State: Situation-Aware Modeling for Air Traffic Flow Prediction
AeroSense directly models microscopic aircraft states with masked self-attention to predict heterogeneous air traffic flows, outperforming time series baselines on real airport data.