A Stochastic Characterization Based Data Mining Implementation for Airport Arrival and Departure Delay Data

Qian Wu

doi:10.4028/www.scientific.net/AMM.668-669.1037

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 668-669A Stochastic Characterization Based Data Mining...

A Stochastic Characterization Based Data Mining Implementation for Airport Arrival and Departure Delay Data

Abstract:

The probabilistic distribution of Airport arrival and departure delays over a selected period of eight months was analyzed using an optimal Generalized Extreme Value (GEV) model in this paper. It is anticipated that quantitative stochastic characterizations of delay data out of our work would improve demand predictions in air traffic flow management systems. Analysis and verification through application of Beijing Capital International Airport’s history flight delay data demonstrate better Goodness of Fit of our optimal GEV based model.

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Periodical:

Applied Mechanics and Materials (Volumes 668-669)

Pages:

1037-1040

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.668-669.1037

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Online since:

October 2014

Authors:

Qian Wu

Keywords:

Air Traffic Flow Management, Flight Delay Prediction, Generalized Extreme Value Model, Probabilistic Distribution

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References

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