DocumentCode :
612667
Title :
Robust Parametric Empirical Bayes based anomaly detection for flight safety events
Author :
Yelundur, A. ; Campbell, K.
Author_Institution :
MITRE/CAASD, McLean, VA, USA
fYear :
2013
fDate :
22-25 April 2013
Firstpage :
1
Lastpage :
8
Abstract :
Control Charts using Parametric Empirical Bayes (PEB) based on a Robust Cauchy prior and Poisson likelihood have proven useful for automatically detecting spikes in safety-related flight operations event rates. As part of the monitoring work of the Aviation Safety Information Analysis and Sharing (ASIAS) program, a joint government-aviation industry program, many hundreds of time series are being monitored. Automated detection methods are a necessity, and control charts a logical choice of tool, but basic control charts are problematic. For example, proportions charts produce excessive alerts. The robust Cauchy-Poisson PEB approach using numerical optimization is efficiently producing manageable numbers of relevant alerts while remaining relatively simple to administer and interpret.
Keywords :
Bayes methods; aerospace safety; control charts; stochastic processes; time series; ASIAS program; Poisson likelihood; automated detection method; aviation safety information analysis and sharing; control charts; flight safety events; government aviation industry program; numerical optimization; robust Cauchy prior; robust Cauchy-Poisson PEB; robust parametric empirical Bayes based anomaly detection; safety related flight operation event rate; time series; Airports; Control charts; Market research; Monitoring; Robustness; Time series analysis; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Integrated Communications, Navigation and Surveillance Conference (ICNS), 2013
Conference_Location :
Herndon, VA
ISSN :
2155-4943
Print_ISBN :
978-1-4673-6251-1
Type :
conf
DOI :
10.1109/ICNSurv.2013.6548562
Filename :
6548562
Link To Document :
بازگشت