Research On Identification Method Of Important Nodes In Complex Networks

With the rise of complex network research,people's life and production activities are increasingly dependent on the safe,reliable and efficient operation of a variety of complex systems.In the real world,the vast majority of complex systems can be abstracted into complex networks,the research on the theory of complex networks can help people to understand the properties and evolution laws of complex systems.In the research of complex network theory,the identification of important nodes has become one of the key research directions.In order to identify the important nodes in complex networks accurately and effectively,the following work has been carried out in this paper:Firstly,this paper analyzes the research background and significance of this paper,by reading and combing the relevant literature,puts forward the problems existing in the important node identification method of complex network,and expounds the basic theory and method of complex network involved in this paper.Secondly,for undirected-unweighted complex networks,considering the importance of nodes and the contribution of associated nodes to their importance,an important node identification method based on importance transfer matrix is proposed.This method is applied to undirected-unweighted ARPA networks.The destructive simulation analysis of the network is carried out according to the identification results,and compared with different methods,it is found that deleting nodes according to this method can cause more damage to the network.The experimental results show the effectiveness of the proposed method for identifying important nodes in complex networks.Furthermore,the important node identification method is applied to the actual undirected-unweighted Hamster social relationship network,using the Gephi network simulation software to count the relevant characteristics of the network and carry out deliberate attacks and random failures on the network.By comparing and analyzing the changes of network robustness and vulnerability,it is found that the proposed method increases the average path length of the network,the number of connected subgraphs is larger,and the scale of connected subgraphs is smaller.The experimental results show once again the applicability and effectiveness of the important node identification method proposed in this paper in practical complex networks.Finally,for directed-weighted complex networks,considering the influence of edge weight and direction on node importance,a directed-weighted complex network important node identification method based on relative importance difference is proposed.The important node identification method is applied to the directed-weighted ARPA network.The destructive simulation analysis of the network is carried out according to the identification results,and compared with different methods,it is found that deleting the node according to this method can cause more damage to the network.The experimental results show the accuracy of the important node identification method proposed in this paper.Furthermore,the important node identification method is applied to the actual directed-weighted US Air Lines network,using the Gephi network simulation software to count the relevant characteristics of the network and carry out deliberate attacks and random failures on the network.By comparing and analyzing the changes of network robustness and vulnerability,it is found that the proposed method increases the average path length of the network,the number of connected subgraphs is larger,and the scale of connected subgraphs is smaller.The experimental results further show the applicability and effectiveness of the important node identification method proposed in this paper in practical directed-weighted complex networks.