DocumentCode :
3398682
Title :
A statistical learning approach to the modeling of aircraft taxi time
Author :
Jordan, Richard ; Ishutkina, Mariya A. ; Reynolds, Tom G.
Author_Institution :
MIT Lincoln Lab., Lexington, MA, USA
fYear :
2010
fDate :
3-7 Oct. 2010
Abstract :
Modeling aircraft taxi operations is an important element in understanding current airport performance and where opportunities may lie for improvements. A statistical learning approach to modeling aircraft taxi time is presented in this paper. This approach allows efficient identification of relatively simple and easily interpretable models of aircraft taxi time, which are shown to yield remarkably accurate predictions when tested on actual data.
Keywords :
air traffic control; airports; learning (artificial intelligence); statistical analysis; aircraft taxi time; airport performance; statistical learning; Aircraft; Airports; Atmospheric modeling; Mathematical model; Predictive models; Training; Variable speed drives;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Avionics Systems Conference (DASC), 2010 IEEE/AIAA 29th
Conference_Location :
Salt Lake City, UT
ISSN :
2155-7195
Print_ISBN :
978-1-4244-6616-0
Type :
conf
DOI :
10.1109/DASC.2010.5655532
Filename :
5655532
Link To Document :
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