交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (6): 189-195.

• 系统工程理论与方法 • 上一篇    下一篇

基于机场延误预测的航班计划优化研究

吴薇薇*,孟亭婷,张皓瑜   

  1. 南京航空航天大学民航学院,南京210016
  • 收稿日期:2016-04-26 修回日期:2016-08-07 出版日期:2016-12-25 发布日期:2016-12-26
  • 作者简介:吴薇薇(1972-),女,安徽宣城人,副教授,博士.
  • 基金资助:

    国家自然科学基金项目/National Natural Science Foundation of China(71201081);南京航空航天大学重点科研专项项目/Key Scientific Research Projects of NUAA(NZ2016109).

Flight Plan Optimization Based on Airport Delay Prediction

WUWei-wei, MENG Ting-ting, ZHANG Hao-yu   

  1. School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2016-04-26 Revised:2016-08-07 Online:2016-12-25 Published:2016-12-26

摘要:

随着航空运输业的快速发展,航班延误及传播问题越来越严重.本文建立基于航班串的贝叶斯网络模型模拟航班延误波及和航班间延误的相互关系,揭示不正常运营条件对航班计划可靠性的影响.根据对航班运营可靠性的分析找出航班串中的薄弱环节,即关键机场,运用加权马尔科夫链模型对关键机场的整体延误状态进行预测,反映机场随机因素对航班串中延误传播的影响.从而更准确地预测航班延误状况,并根据预测结果对航班计划进行相应调整,以提高航班计划运营可靠性.

关键词: 航空运输, 航班计划优化, 贝叶斯网络, 马尔科夫链, 延误波及

Abstract:

With the rapid development of air transport industry, the problem of flight delay and propagation is becoming more and more serious. In this paper, a Bayesian network model based on flight string is established to simulate the relationship between delay propagation and flight delays, and to indicate the impact of abnormal operation conditions on the reliability of the flight plan. According to the reliability of flight operations, we find out the weak link of string, namely the key airport. And by using the weighted Markov chain model to predict overall delayed state of the key airport, reflecting the impact of airport random factors on the spread of flight delays in the string. Therefore, it is more accurate to predict the flight delay. According to the forecast results, the flight plan is adjusted accordingly, so as to improve the reliability of the flight plan.

Key words: air transportation, flight plan optimization, Bayesian networks, Markov chain, delay propagation

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