Research On Key Node Of Multi-Layer Transportation Network Based On Complex Network Theory

With the rapid development of science and technology in China,the continuous construction of infrastructure has gradually formed many relatively large network systems,and various large-scale network systems have been integrated into our lives.In real life,different networks interact with each other,and the coupling between different networks will form a large-scale multi-layer network.One of the most representatives is the transportation networks.In order to improve transportation efficiency,different types of traffic networks are coupled to form a multi-layer transportation network.Some nodes in multi-layer transportation network lose transportation capacity due to external factors,and cascading effects may occur in the network to reduce the transportation efficiency of the network.Therefore,in order to improve the invulnerability and robustness of multi-layer transportation network,it is necessary to accurately identify key node in multi-layer transportation network.Nowadays,most of the research on key node is still on a single-layer network.According to the above problem,based on the background of multi-layer transportation network,this paper focuses on the key node of multi-layer transportation network.We use the theory of network science,the key node of multi-layer transportation network is studied from the perspectives of damage and repair,and the corresponding identification methods are proposed.The work content and research results of this paper are as follows:1.Research on key damage node.According to the topological structure characteristics of the actual aviation network and railway network,different network models are used to construct a multi-layer transportation network with aviation and railway as the transportation mode.In the multi-layer transportation network,the intra-layer edges and the inter-layer edges have corresponding transportation costs,and specifying the route transportation load between nodes according to the minimum total transportation cost.The network carrying capacity,that is,the maximum load of transportation under normal conditions of the network,is used to evaluate the transportation performance of the network.Due to the internal load of multi-layer transport network,the topological characteristics of the network cannot be considered only when identifying key damage node.Therefore,this paper proposes a method to identify the degree information of the integrated node and its local load information.The damage of different node has different effects on network performance,the network carrying capacity after damage is used as an evaluation index to reflect the importance of node.The simulation results show that compared with other methods,the identification method proposed in this paper can effectively find the key damage node of multi-layer transportation network in different transportation situation.2.Research on key repair node.In the case of limited repair resources,how to quickly identify the best repair node from some failure nodes becomes necessary.Therefore,this paper proposes a method to identify key repair node.This method combines the location factors of the failure node and the load around the failure node.The importance of the failure node is evaluated from the network topology and the internal load information of the network.In order to compare the effect of different methods to identify key repair node,this paper uses the network carrying capacity after repair,the increase rate of network carrying capacity and the probability of identifying the best repair node as evaluation indexes.Finally,the simulation results show that compared with other methods,the key repair node identification method proposed in this paper can accurately find the key repair node from some failure nodes in different transportation situation.3.Application of identification methods.A multi-layer transportation network is constructed based on real flight information and railway information.The two key node identification methods proposed in this paper are applied to the actual network.The experimental results further verify the effectiveness of the two key node identification methods proposed in this paper.In order to further understand the process of internal transportation in the network,some transportation routes are visualized.We demonstrate the changes in the transport path of the network after damage and repair.This helps to better understand the transport process within the network.