基于贝叶斯网络的机场航班延误因素分析

中国民航业近年来快速发展,航班量增多、航班密度逐步加大,许多资源配置的矛盾也日益凸显出来。机场大面积航班延误难以避免。针对上述问题,在航班延误波及分析的基础上,建立机场航班延误的贝叶斯网络分析模型。通过机场航班数据网络学习和测试,得到了不同因素对机场航班延误的影响程度、不同时间段的延误情况,为机场当局解决大面积航班延误提供决策依据。

The Analysis of Flight Delay in Airport Based on Bayesian Networks

The flight quantity and density have increased gradually and the contradiction of resource allocation became prominent with the rapid development of China civil aviation in recent years. The difficulties encountered by airspace and airport while meeting the growing flights and the effects that random factors, such as weather, posed on regular airline and airport operations make large area flight delay difficult to prevent. Large area flight delay not only produced great economy losses to airlines and airports and negative effects to the civil aviation reputation, but also raised the possibility for terminal mass disturbance which might turn the terminal in chaos and risk the airport operation security. The Bayesian network model of the airport flight delay was proposed on the basis of flight delay analysis for the above problems. The complexity of flight delay respond to different factors get understood by the study and tests of airport flight data network, which provides decision foundations for airport authorities to settle large area flight delay down.