Graph time-series mixture models for air traffic prediction

Conclusion and Future Work Network analysis of inter-airport traffic using FAAs traffic flow management data stream Found daily graph clustering properties to differ from previously reported results (due to limits of those data sets) Quantified temporally complex behavior, which contains a significant non-weekly trend Spectral Analysis Dominant eigenvectors are quasi-stationary Low rank spectral models capture bulk of daily network power Preliminary analysis suggests utility of model in forecasting Correlation analysis suggests alternative approach for network decomposition (future work).