基于随机集贝叶斯网的航班延误分析
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摘要
针对鲜有研究的航空联盟对航班延误的影响以及航空联盟与延误成因的组合关系,基于贝叶斯网络原理和随机集理论,分别在完整样本和仅有统计信息的情况下对航空公司的航班运行情况进行贝叶斯建模.通过对加入航空联盟前后的延误情况进行对比分析、敏感性分析及与其他影响航班延误的关键因素进行组合分析,指出基于随机集贝叶斯建模的方法能为延误分析提供支持;加入航空联盟后,航班延误的整体情况得到改善;相对其他不可控的影响因素,航空联盟、航空公司自身因素的组合改善能有效地减少延误.
In order to evaluate the impacts of airline alliances on flight delays and the combined effects of alliances with different factors which were barely investigated,according to Bayesian network and random set theory,the Bayesian models of flight delay analysis were separately built based on abundant samples and only statistics.Throughout the research,the extent of flight delays before and after joining the alliance was compared and their sensitivity was analyzed,as well as the combination of other key factors.The results indicate that the proposed method can strongly support the delay analyse and decision.The flight delay status tends to improve after joining the alliance.The combined improvements of the alliance and airlines can effectively ameliorate the impacts of flight delays relative to other uncontrollable factors.
In order to evaluate the impacts of airline alliances on flight delays and the combined effects of alliances with different factors which were barely investigated,according to Bayesian network and random set theory,the Bayesian models of flight delay analysis were separately built based on abundant samples and only statistics.Throughout the research,the extent of flight delays before and after joining the alliance was compared and their sensitivity was analyzed,as well as the combination of other key factors.The results indicate that the proposed method can strongly support the delay analyse and decision.The flight delay status tends to improve after joining the alliance.The combined improvements of the alliance and airlines can effectively ameliorate the impacts of flight delays relative to other uncontrollable factors.
引文
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[2]曹卫东,丁建立,刘玉洁.基于贝叶斯网络的航班离港延误预警分析[J].计算机应用研究,2008,25(11):3388-3390.14
[3]丁建立,赵键涛,曹卫东,等.基于动态贝叶斯网的航班延误传递分析[J].计算机工程与设计,2015(12):3312-3316.
[4]杨秀云,王军,何建宝.航班延误关键影响因素及影响程度识别-基于动态排队模型的分析[J].统计与信息论坛,2014,29(4):88-95.
[5]RUTNER S M,WHITAKER J.Alternatives for reducing delays at the United States'busiest airports[J].Transportation Journal,1997,36(3):18-25.
[6]SCHAEFER L,MILLNER D.Flight delay propagation analysis with the detailed policy assessment tool[C].Proceedings of the 2001IEEE Systems,Man,and Cybernetics Conference,USA,2001.
[7]WONG J T,TSAI S C.A survival model for flight delay propagation[J].Journal of Air Transport Management,2012,23(7):5-11.
[8]PYRGIOTIS N,MALONE K M,ODONI A.Modelling delay propagation within an airport network[J].Transportation Research Part C Emerging Technologies,2013,27(2):60-75.
[9]张连文.贝叶斯网引论[M].北京:科学出版社,2006.
[10]兰旭辉,熊家军,陈劲松,等.基于随机集的多源信息表示方法[J].数据采集与处理,2012(S1):24-27.
[11]徐晓滨.不确定性信息处理的随机集方法及在系统可靠性评估与故障诊断中的应用[D].上海:上海海事大学,2009.
[12]赵亮.基于随机集理论的QMU关键技术研究[D].北京:中国工程物理研究院,2016.
[13]梁吉业,冯晨娇,宋鹏.大数据相关分析综述[J].计算机学报,2016(1):1-18.