工程科学学报.第44卷.第1期：114-121.2022年1月 Chinese Journal of Engineering,Vol.44,No.1:114-121,January 2022 https://doi.org/10.13374/j.issn2095-9389.2020.06.15.002;http://cje.ustb.edu.cn 基于有向权值网络的航班运行风险传播与控制 王岩韬四，杨志远，刘锟，谢春生 中国民航大学航空公司人工智能民航局重点实验室，天津300300 ☒通信作者，E-mail:caucwyt@126.com 摘要为了分析航班运行风险传播过程，进而有效控制保障飞行安全，基于复杂网络理论，首先参照民航局咨询通告选取 机组、航空器、运行环境共29个终端因素作为网络节点，统计民航安全监察记录，根据事件中节点关系，构建无向网络：统计 前后节点间的作用关系和发生概率，提出一种有向带权的航班运行风险网络：然后，引入改进感染率和改进恢复率概念，构建 一种适用于航班运行风险传播分析的改进SIR(Susceptible-infected-recovered)模型；定义感染起始范围，最后采取多参数控制 方式，大规模计算该有向带权网络的传播和控制过程.结果表明：有向网的平均最短路径为1.788，属于小世界网络：参照使用民 航常规管控措施，有向网节点感染下降幅度可达到37.4%：对入度值排序前3或前4的节点控制后，感染节点峰值下降率高达50.6% 和58.1%.网络传播抑制明显.结果证实：在该航班运行风险有向带权网络中，按人度值控制节点对抑制风险传播最为有效 关键词航空运输：航班运行风险：复杂网络：有向带权网络：改进SR模型 分类号N945.24:U8:V355.2 Flight operation risk propagation and control based on a directional-weighted complex network WANG Yan-tao,YANG Zhi-yuan,LIU Kun,XIE Chun-sheng Airlines Artificial Intelligence Key Laboratory of Civil Aviation Administration,Civil Aviation University of China,Tianjin 300300,China Corresponding author,E-mail:caucwyt@126.com ABSTRACT The flight operation risk is equal to the occurrence probability multiplied by the severity of the consequences.Flight operation risks include many types,forms,and numbers,and they frequently change with conditions.In the face of this complex system, through principle analysis,the risk formation mechanism research,and the spreading process,a scientific risk management and control method can be constructed.Based on the risk management technology,an informative and automated management control system can be developed and applied.The overall safety level of flight operations will be effectively improved.To analyze and study the flight operations risk propagation and then effectively control flight safety based on the complex network theory,29 terminal factors were selected as network nodes according to the Civil Aviation Administration's advisory notice,initially including the flight cabin crew,civil aviation aircraft,and operating environment.Civil aviation safety monitoring records from 2009 to 2014 were counted,and an undirected network was constructed based on node relationships.The relationships and occurrence probability between the nodes were counted,and a directed and weighted network was constructed.The concepts of improved infection rate and improved recovery rate were introduced,and an improved susceptible-infected-recovered(SIR)model suitable for flight operation risks was proposed.Finally,the initial infection range was clearly defined,and a multi-parameter control method was adopted.For directed networks,large-scale propagation and control simulations were calculated.The results indicate that the average shortest path of the directed network was 1.788,which belonged to the small-world network.The directed network infection node decreased to 37.4%with conventional control measures.After controlling top three or four nodes of the entry degree value sequence,the infected nodes peak drop rate was the biggest, 收稿日期：2020-06-15 基金项目：国家自然科学基金资助项目(01933103)基于有向权值网络的航班运行风险传播与控制 王岩韬苣，杨志远，刘    锟，谢春生 中国民航大学航空公司人工智能民航局重点实验室，天津 300300 苣通信作者， E-mail：caucwyt@126.com 摘    要    为了分析航班运行风险传播过程，进而有效控制保障飞行安全，基于复杂网络理论，首先参照民航局咨询通告选取 机组、航空器、运行环境共 29 个终端因素作为网络节点，统计民航安全监察记录，根据事件中节点关系，构建无向网络；统计 前后节点间的作用关系和发生概率，提出一种有向带权的航班运行风险网络；然后，引入改进感染率和改进恢复率概念，构建 一种适用于航班运行风险传播分析的改进 SIR(Susceptible-infected-recovered) 模型；定义感染起始范围，最后采取多参数控制 方式，大规模计算该有向带权网络的传播和控制过程. 结果表明：有向网的平均最短路径为 1.788，属于小世界网络；参照使用民 航常规管控措施，有向网节点感染下降幅度可达到 37.4%；对入度值排序前 3 或前 4 的节点控制后，感染节点峰值下降率高达 50.6% 和 58.1%，网络传播抑制明显. 结果证实：在该航班运行风险有向带权网络中，按入度值控制节点对抑制风险传播最为有效. 关键词    航空运输；航班运行风险；复杂网络；有向带权网络；改进 SIR 模型 分类号    N945.24；U8；V355.2 Flight operation risk propagation and control based on a directional-weighted complex network WANG Yan-tao苣 ，YANG Zhi-yuan，LIU Kun，XIE Chun-sheng Airlines Artificial Intelligence Key Laboratory of Civil Aviation Administration, Civil Aviation University of China, Tianjin 300300, China 苣 Corresponding author, E-mail: caucwyt@126.com ABSTRACT    The  flight  operation  risk  is  equal  to  the  occurrence  probability  multiplied  by  the  severity  of  the  consequences.  Flight operation risks include many types, forms, and numbers, and they frequently change with conditions. In the face of this complex system, through principle analysis, the risk formation mechanism research, and the spreading process, a scientific risk management and control method can be constructed. Based on the risk management technology, an informative and automated management control system can be developed  and  applied.  The  overall  safety  level  of  flight  operations  will  be  effectively  improved.  To  analyze  and  study  the  flight operations  risk  propagation  and  then  effectively  control  flight  safety  based  on  the  complex  network  theory,  29  terminal  factors  were selected as network nodes according to the Civil Aviation Administration’s advisory notice, initially including the flight cabin crew, civil aviation  aircraft,  and  operating  environment.  Civil  aviation  safety  monitoring  records  from  2009  to  2014  were  counted,  and  an undirected network was constructed based on node relationships. The relationships and occurrence probability between the nodes were counted, and a directed and weighted network was constructed. The concepts of improved infection rate and improved recovery rate were introduced, and an improved susceptible-infected-recovered (SIR) model suitable for flight operation risks was proposed. Finally, the initial  infection  range  was  clearly  defined,  and  a  multi-parameter  control  method  was  adopted.  For  directed  networks,  large-scale propagation  and  control  simulations  were  calculated.  The  results  indicate  that  the  average  shortest  path  of  the  directed  network  was 1.788, which belonged to the small-world network. The directed network infection node decreased to 37.4% with conventional control measures. After controlling top three or four nodes of the entry degree value sequence, the infected nodes peak drop rate was the biggest, 收稿日期: 2020−06−15 基金项目: 国家自然科学基金资助项目（U1933103） 工程科学学报，第 44 卷，第 1 期：114−121，2022 年 1 月 Chinese Journal of Engineering, Vol. 44, No. 1: 114−121, January 2022 https://doi.org/10.13374/j.issn2095-9389.2020.06.15.002; http://cje.ustb.edu.cn