Evaluation Method Of Node Importance In Complex Network Based On Multi-index Fusion

With the progress and rapid development of the network information age,various organizations and economic activities of human society in real life tend to be networked,such as transportation network,power transmission network,social information network and biological resources network.Key nodes play an important role in the normal operation of the network.Accurate identification of key nodes in the complex network is of great significance to improve the network survivability and ensure the safe and efficient operation of the network system.In view of the limitations of single node importance index in the process of evaluating the node importance of complex networks,this paper carries out the research on the evaluation method of node importance of complex networks with multi index characteristics under the concept of multi index fusion.(1)This paper discusses the existing evaluation methods of node importance,and analyzes the advantages and disadvantages of various algorithms.In order to evaluate the performance of complex networks,this paper constructs the evaluation index system of basic topological characteristics of complex networks,analyzes the characteristics of basic models of complex networks,and constructs the evaluation index set of node importance of complex networks.(2)The TOPSIS method and dynamic index set are used to evaluate the importance of nodes in complex networks.In this method,each node in the network is regarded as a scheme in TOPSIS,and each importance evaluation index is regarded as the attribute of the scheme.According to the characteristics of the network,the importance evaluation index is dynamically selected,and the node importance calculation is regarded as a multi-attribute evaluation problem.Through the intentional attack experiments in four real networks,the average path length,network diameter,maximum connectivity and network efficiency are obtained.The results show that the proposed method has a greater impact on network performance than other classical evaluation indexes.(3)This paper proposes a node importance evaluation method based on multi-level neighbor contribution.From the perspective of the contribution of neighbor nodes to the target nodes,the K-shell index is introduced to establish the contribution coefficient matrix,and the importance evaluation model is constructed by combining multiple importance evaluation indexes.Through the SIR propagation model in eight real networks,the results show that the proposed method can accurately evaluate the importance and influence of nodes in the network compared with other classical evaluation indexes.