2023Unpublished venueRequires access

Research on Prediction Model of Flight Departure Runway

Hu Qisong, Zixuan Wu, Wen Yin, Chen Guoqiang, Yun Zou

Open publisher page 2 citations

Abstract

The takeoff runway is an important part of the new generation flight plan making software. The selection of flight takeoff runway is mainly affected by flight plan, weather, terminal area operation and other factors, which is a nonlinear classification decision problem in complex scenarios. In recent years, the data driven artificial intelligence method has been used in the operation decision-making of civil aviation. In this paper, a neural network algorithm based on artificial intelligence is proposed to construct a flight takeoff runway prediction model considering business experience and rules. The model is validated with the historical flight operation data of Xiamen Airport, and the results show that the model is accurate and effective.

About this research paper

What this paper is about

The takeoff runway is an important part of the new generation flight plan making software. The selection of flight takeoff runway is mainly affected by flight plan, weather, terminal area operation and other factors, which is a nonlinear classification decision problem in complex scenarios. In recent years, the data driven artificial intelligence method has been used in the operation decision-making of civil aviation. In this paper, a neural network algorithm based on artificial intelligence is proposed to construct a flight takeoff runway prediction model considering business experience and rules. The model is validated with the historical flight operation data of Xiamen Airport, and the results show that the model is accurate and effective.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The takeoff runway is an important part of the new generation flight plan making software. The selection of flight takeoff runway is mainly affected by flight plan, weather, terminal area operation and other factors, which is a nonlinear classification decision problem in complex scenarios. In recent years, the data driven artificial intelligence method has been used in the operation decision-making of civil aviation. In this paper, a neural network algorithm based on artificial intelligence is proposed to construct a flight takeoff runway prediction model considering business experience and rules. The model is validated with the historical flight operation data of Xiamen Airport, and the results show that the model is accurate and effective.

Key concepts: Runway, Takeoff, Flight plan, Artificial neural network, Civil aviation, Computer science, Takeoff and landing, Air traffic control

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