计算机科学 ›› 2019, Vol. 46 ›› Issue (10): 329-335.doi: 10.11896/jsjkx.181102039

• 交叉与前沿 • 上一篇    

基于贝叶斯网络的航班离港时间动态估计

邢志伟1, 朱慧1, 李彪1, 罗谦2   

  1. (中国民航大学电子信息与自动化学院 天津300300)1
    (中国民航局第二研究所工程技术研究中心 成都610041)2
  • 收稿日期:2018-11-05 修回日期:2019-02-14 出版日期:2019-10-15 发布日期:2019-10-21
  • 通讯作者: 李彪(1993-),男,硕士生,主要研究方向为机场交通信息与控制,E-mail:18330227730@163.com。
  • 作者简介:邢志伟(1970-),男,博士,教授,主要研究方向为民航装备与系统、机场交通信息与控制;朱慧(1995-),女,硕士生,主要研究方向为机场交通信息与控制;罗谦(1975-),男,博士,研究员,主要研究方向为机场运营管理。
  • 基金资助:
    本文受国家自然科学基金(U1533203),中央高校基本科研业务费资助项目(ZYGX2018037)资助。

Dynamic Estimation of Flight Departure Time Based on Bayesian Network

XING Zhi-wei1, ZHU Hui1, LI Biao1, LUO Qian2   

  1. (College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China)1
    (Engineering Technology Research Center,The Second Research Institute of CAAC,Chengdu 610041,China)2
  • Received:2018-11-05 Revised:2019-02-14 Online:2019-10-15 Published:2019-10-21

摘要: 为了准确地感知航班离港流程和估计航班离港的时间,设计了一种基于动态贝叶斯网络的航班离港时间估计方法。首先,基于航班的不同属性分析影响航班离港流程的因素,根据影响因素对数据进行分类处理,在历史数据分类的基础上,结合蒙特卡洛模拟方法获取各环节的联合分布和先验分布,并由柯尔莫哥洛夫检验确定各环节的联合分布模型,从而获得动态贝叶斯网络模型的参数;其次,根据贝叶斯网络架构和条件概率推理动态估计离港时间及各环节的完成时间;最后,选取国内中部某机场的单航班离港运行数据进行仿真验证。研究结果表明:随着流程的推进,其传播误差会增大,但离港时间的估计精度达到了80%以上,动态估计结果的稳定性较好,能够充分地反映航班离港流程中各关键节点的实际情况。

关键词: 传播误差, 动态贝叶斯网络, 航班离港, 航空运输, 柯尔莫哥洛夫检验, 条件概率估计

Abstract: In order to accurately perceive the flight departure process and estimate the flight departure time,a method for estimating flight departure time based on dynamic Bayesian network was designed.Firstly,the factors affecting the flight departure process are analyzed based on different flight attributes.According to the influencing factors,the data are classified and processed,and the Monte Carlo simulation method is combined with the historical data classification to obtain the joint and prior distribution of each link.The Kolmogorov test is used to determine the joint distribution model of each link,and the parameters of the dynamic Bayesian network modelare obtained.Secondly,the Bayesian network architecture and conditional probability are used to infer the dynamic estimation of the departure time and the completion time of each link.Finally,the single-destination operation data of an airport in the middle of the country are selected for simulation verification.The research results show that with the progress of the process,the propagation error will gradually increase,and the estimated accuracy of the departure time will be over 80%,what’s more,the stability of the dynamic estimation result will be better,which can fully reflect the actual situation of the key node in the departure process of the flights.

Key words: Air transportation, Conditional pro-bability estimation, Dynamic Bayesian network, Flight departure process, Kolmogorov test, Propagated error

中图分类号: 

  • TP181
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