Research On The Transmit Model Of The Large-Area Flight Delays’ Propagation And Transfer In The Hub Airport

The hub Airports play an increasingly important role in the modern air transport style.But its frequent flight delays’ spread has also become a focus of attention. The inbound and outbound flights and ground transit operations in the hub airport formed a special flight chain.The arrival delays’ propagation and transfer will happen. From the perspective of hub airports,this thesis takes the bayesian theory and hazard models to model the matter. It also combines the consideration of important factors for affecting the airdrome flight delays. It would make real-time prediction for flights delay, around arrival flights and departure flights. The main research work of this dissertation is as follows:First, it analysis the regularity of hub airport delays and makes a large hub airport for domestic actual data for the analysis of statistics. So it can get the delay probability distribution of the propagation and transfer for the inbound flight delay. Second, taking into account the complexity for the problem of the hub airport flight delays’ propagation and transfer, it uses the Bayesian networks which combines the Bayesian probabilistic methods and directed acyclic graph of network topology to model. A large number of experimental results on domestic hub airports show that the model is more adaptive and real-time. It predicts the flight delays’ propagation and transfers based on the theory of adaptive immune algorithm. Consider the similarity of the flight delays and the state of the immune system antigen recognition. It establishes a set of flights for delays in the membership function, use the large hub airport domestic actual operating data to train the detector to build a large hub airport flight delays’ propagation and transfer model. The model’ validity were verified by the actual data from the large hub airport of domestic, The methodology and research results have important value of application for the present hot issue of flight delays forecast warning.