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).


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    Title :

    Graph time-series mixture models for air traffic prediction


    Contributors:


    Publication date :

    2013-04-01


    Size :

    1878793 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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