Complex Network Model Based on Node Attraction with Tunable Parameters

According to the evolution rule of real-world networks and aiming at the problems existing in preferential attachment and statistical characteristics of network in BA model and initial attractive model, taking into account preferential attachment of node degree and node attraction in the evolution process of complex network, a complex network model based on node attraction with tunable parameters was proposed. Theory research and simulation analysis show the fact that the complex network model based on node attraction with tunable parameters can effectively generate networks with stable structure and actual statistical characteristics. Specifically, the degree distribution of networks still follows power-law distribution, while clustering coefficient and average path length are high.