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Aug 30, 2023
Delay Prediction of Flight Operation Network Based on Deep Learning Combination Model
Authors: Jiaxin Chen [email protected], Weiwei Wu [email protected], Wenbin Wei [email protected], and Jiahui Yu [email protected]Author Affiliations
Publication: CICTP 2023
ABSTRACT
Due to the correlation between flights in the airline’s flight operation network, when a flight delay occurs, it usually leads to a wide range of delay propagation. In this paper, a GCN-GRU combined prediction model is proposed to predict the level of departure delay owing to the constraints of the airline flight operation network topological structure and the law of dynamic change with time. Specifically, a graph convolution network (GCN) is used to capture the spatial characteristics of flight delay propagation and the gated recurrent unit (GRU) is used to capture the temporal characteristics of flight delay. Experiments show that the GCN-GRU model can obtain the spatio-temporal features from flight delay data. And on real-world flight delay data sets, the prediction results are better than state-of-art baselines. In addition, the experimental results are analyzed by using complex network theory, and the applicability of the model is obtained.
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Published online: Aug 30, 2023
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ASCE Technical Topics:
- Aerospace engineering
- Air transportation
- Aircraft and spacecraft
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Continuum mechanics
- Correlation
- Dynamic models
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Flight
- Information management
- Infrastructure
- Mathematics
- Models (by type)
- Neural networks
- Solid mechanics
- Statistics
- Structural dynamics
- Structural models
- Transportation engineering
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1College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Nanjing, China. Email: [email protected]
2College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Nanjing, China. Email: [email protected]
3Dept. of Aviation and Technology, San Jose State Univ., San Jose, CA. Email: [email protected]
4College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Nanjing, China. Email: [email protected]
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