AeroSense directly models microscopic aircraft states with masked self-attention to predict heterogeneous air traffic flows, outperforming time series baselines on real airport data.
Deep learning based short-term air traffic flow prediction considering temporal–spatial correlation.Aerospace Science and Technology, 93:105113
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.