Abstract
Flight delay prediction remains an important research topic due to its dynamic nature. Dynamic data-driven approach might provide a solution to this problem. To apply the approach, a flight delay state-space model is required to represent relationship among system states, as well as relationship between system states and input/output variables. Based on the analysis of delay event sequence, a state-space model was established and the input variable was studied. A genetic EM algorithm was applied to obtain global optimal estimates of parameters used in the mode. Validation based on probability interval tests shows that: the model has reasonable goodness of fit to the historical flight data, and the search performance of traditional EM algorithm can be improved by ideals of Genetic Algorithm.
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Chen, H., Wang, J., Yan, H. (2011). Modeling of Flight Delay State-Space Model. In: Lin, S., Huang, X. (eds) Advanced Research on Computer Education, Simulation and Modeling. CESM 2011. Communications in Computer and Information Science, vol 175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21783-8_5
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DOI: https://doi.org/10.1007/978-3-642-21783-8_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21782-1
Online ISBN: 978-3-642-21783-8
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