Research on GRNN Model for Short-Term Air Traffic Flow Management

Zhan Wang; Shu Wu

doi:10.4028/www.scientific.net/AMM.263-266.3244

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Research on GRNN Model for Short-Term Air Traffic...

Research on GRNN Model for Short-Term Air Traffic Flow Management

Abstract:

For the exigent requirement of short-term air traffic flow optimized dispatching, this paper analyzes dynamic behavior and network flow algorithm of short-term air traffic flow management, presents evacuation based ST-TFMP dynamic network flow algorithm, builds ST-TFMP GRNN model. The model is verified by simulation experiment, the results show it is feasible. The model improves precision of short-term air traffic flow management, saves time and cost, and it also actualizes the intelligence short-term air traffic flow management.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

3244-3249

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.3244

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Online since:

December 2012

Authors:

Zhan Wang, Shu Wu

Keywords:

Artificial Intelligence System, Dynamic Network Flow, General Regression Neural Network (GRNN), Short-Term Traffic Flow Management (ST-TFMP)

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References

[1] O doni A R. The flow management problem in air traffic control[A]. O doni A R, Szego G. Flow Control of Congested Networks[C]. Berlin: Spring-Verlag, 1987. 269-298.

DOI: 10.1007/978-3-642-86726-2_17

Google Scholar

[2] Stock-Patterson S. Dynamic Flow Management Problems in Air Transportation[D]. Cambridge: MIT, 1997.

Google Scholar

[3] V ranas P. Optimal slot allocation for european air traffic flow management[J]. Air Traffic Control,1997, 4(4):249-280.

DOI: 10.2514/atcq.4.4.249

Google Scholar

[4] Cheng peng, Cui de-guang, Wu-Cheng journal of tsinghua university [J] 2000, Vol 40, No.11.

Google Scholar

[5] Cai zi-xing, Xu guang-you. Artificial Intelligence: Principles and Applications. (2004)

Google Scholar

[6] Zhang honghai, Hu minghua. Dynamic coordination trading slot MAS-based in collaborative ground delay airport[J]. Journal Of Systems Engineering, 2010, 25(3):394-400.

Google Scholar