Machine learning

Optics

Physics

Granger causality

Network delay

Artificial intelligence

Network packet

Nonlinear system

Control (management)

Construct (python library)

Computer network

Computer science

Wave propagation

Control theory (sociology)

Quantum mechanics

Causality (physics)

Propagation delay

Transportmetrica B Transport Dynamics

To probe deeply into the underlying mechanism of flight delay propagation, we construct the delay propagation networks among airports via refined nonlinear Granger causality, which is more fitting on nonlinear airport delay data and obtain more precise causal estimation. Specifically, the causal analysis method is used to determine the delay propagation relationship between airports. The delay propagation relationship of these airport pairs constitutes an airport delay propagation network, in which the nodes and edges of the network, respectively, represent the specific airport and the delay propagation relationship between airports. Complex network theory is then applied to analyse the global structure of delay propagation networks, indicating that small airports are inclined to cause or exacerbate delays. In addition, the airlines’ delay propagation networks display that the delay propagation by large airlines spread wider while the delay propagation by small airlines spread faster. These findings can be employed to design strategies for delay propagation dampening.

Delay propagation network in air transport systems based on refined nonlinear Granger causality