基于机场繁忙程度的航班延误波及分析

The Flight Delay Propagation Analysis based on Airport Busy State

航班延误是全球航空业面临的一大难题。航班运行过程中,对于执行航班环任务的飞机,机场繁忙程度直接影响飞机过站时间长短,进而影响航班离港延误程度。文中构建到港延误对离港延误的波及贝叶斯网络预测模型时,加入机场繁忙程度这一因素,以机场飞机起降架次作为刻画该因素的指标,并通过贝叶斯网络结构学习得到机场繁忙程度的影响关系图。10次10折交叉验证的结果表明,与直接用到港延误预测离港延误的模型相比,加入机场繁忙程度因素的模型能够更准确地预估航班延误波及情况。

Global airline industry has been plagued by flight delays.During the flight operation,for the plane executing flight string tasks,the busy state of airport has a direct effect on the turnaround time of plane,further more effects the on-time departure performance of the consecutive flight.When constructing the prediction Bayesian Network(BN)model of delay propagation,the influence of airport busy state is considered which is described by aircraft movement per hour and whose relative factors are discovered through Bayesian structure learning.The ten times ten-fold cross validation results show that compared with the propagation BN model without consideration of airport busy state,the BN model considering airport busy state shows more accuracy in predicting departure delay.