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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