Research On Complex Network Model For Evolution Of Flight Area Security Risks In Non-stop Flight Construction

With the advancement of civil aviation power strategy,the scale of the industry continues to expand,and the airport support capacity faces higher requirements.In order to meet the surge in airport flight flow without affecting the normal operation of the airport,various reconstruction and expansion projects,such as the prolonging the taxiways and the construction of freighter corridors,have entered a climax.Under the new situation,non-stop flight construction has become one of the airport’s recurring projects.The construction of the flight area involves sensitive areas such as runways,taxiways and electromagnetic protection zones,which increase the possibility and seriousness of safety risk factors such as untimely release of construction information,improper pipeline protection,lack of construction supervision,and insufficient special handling capacity.It is easy to cause insecure events such as runway(sliding lane)intrusion,aircraft intrusion,etc.Once it occurs,it will not only cause loss of resources and property,but may even destroy people.Aiming at the nonlinear and complex relationship between the safety risk factors of the flight area during the non-stop flight construction period,this thesis takes the flight area safety risks during the non-stop flight construction period as the research object,and the complex network evolution model is constructed.Based on the analysis of the network topology characteristics,the possible link relationships between the pairs of unconnected nodes in the network are analyzed.The screening of key risk factors and the prediction of the future evolution path of flight area safety risks in non-stop flight construction are realized.In order to improve the targeted and scientific of security risk management,effectively reduce the impact of non-stop flight construction on the normal operation of the airport,improve the overall safety level of the airport,and enhance the overall support capacity of the airport.The thesis consists of six parts.The first part expounds the purpose and significance of the research,and further determines the research contents and methods based on the review of relevant research at home and abroad.The second part defines the related concepts,analyzes the characteristics of non-stop flight construction,and combs the research basis of safety risk management theory and complex network theory.The third part comprehensively analysis the cases of unsafe construction events in recent years and related investigation and interview data.Through the identification the flight area safety risks during non-stop flight construction period,a model of influencing factors is established by using grounded theory.The Part IV focuses on on the key risk factors in flight area during non-stop flight construction period.Based on the construction of risk evolution network model,Pajek software and R software are used to analyze the network topology,multiple applicability indicators are selected and weighted to construct comprehensive attribute indicators based on DS evidence theory.The Part V builds the evolution model of flight area safety risks during the non-stop flight construction based on link prediction.According to the network topology characteristics,the CNID index is used to predict the link between network nodes,and the accuracy comparison analysis of this method is carried out.The Part VI summarizes the conclusions and the main innovation points of this thesis,sums up the limitations of the research,and proposes the expansion of the follow-up research.The main innovations of this thesis are summed up: the multi-attribute decision-making optimization method for screening the key factors of flight area safety risks in non-stop flight construction is proposed,which reduces the subjectivity of subjective judgment and avoids the one-sidedness of single attribute description;the flight area safety risks evolution prediction model during the non-stop construction period is constructed,and the unknown or future evolutionary link relationship between nodes in the network is explored.