▪ Monitoring needs to produce a small number of alerts that are relatively intuitive to interpret, and likely to be actionable by experts in flight operations ▪ Cauchy — Poisson model is robust enough to: — Apply to all types of safety events — rare or otherwise — Account for over-dispersion in the data as well as deal with spikes in the training period — Effectively filter out nuisance alarms and at the same time be sensitive enough to detect true outliers ▪ Reaction from the customer, CAST Working Group (WG), has been largely positive — Use control charts to monitor the effectiveness of their safety enhancements each quarter ▪ The control charts have been annotated with the Westinghouse Electric alerting rules so a change in the mean could be detected as well ▪ The methodology helped the WG to focus their attention on a limited set of airports with anomalies — Facilitating the understanding of the causal factors and operational procedures causing the anomaly.


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    Titel :

    Robust Parametric Empirical Bayes based anomaly detection for flight safety events


    Beteiligte:
    Yelundur, Anil (Autor:in) / Campbell, Keith (Autor:in)


    Erscheinungsdatum :

    01.04.2013


    Format / Umfang :

    787177 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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