The use of demand correlation in the modeling of air carrier departure delays as first‐order autoregressive random processes |
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Authors: | John H. Mott |
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Affiliation: | Department of Aviation Technology, Purdue University, , Indianapolis, IN, 46241 U.S.A. |
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Abstract: | A method for modeling air carrier departure delays at commercial‐service airports as autoregressive random processes is presented. This method employs the correlation of a priori demand data to significantly reduce prediction error in the optimal least‐squares estimator for additive white noise. The reduction factor of the prediction error is demonstrated to be on the order of 102 over that of the unbiased estimator. Copyright © 2011 John Wiley & Sons, Ltd. |
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Keywords: | air traffic air transportation transport networks airport |
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