Ensemble BDT consistently outperforms the single SVM classifier. This demonstrates that multiple classifier systems are more robust in the presence of noise and other imperfections in data as compared to a single classifier system. • The BDT classifier provides very good estimates of the runway configuration using the airport weather. • The AAR classification predictions by BDT for 2 and 4 hour look-ahead times are excellent. For 6-hour AAR prediction, the performance of the BDT classifier is not bad, AUC is 86% for EWR and 92% for ORD. • The AAR prediction results using BDT models for EWR are not as good as for ORD (Weather factors).


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    Titel :

    Estimate weather impacted airport capacity using ensemble learning


    Beteiligte:
    Wang, Yao (Autor:in)


    Erscheinungsdatum :

    01.10.2011


    Format / Umfang :

    87975 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch