Complex Network Evolution Model Based on Node Attraction

This paper studied the evolution law of the real-world networks, and then proposed a complex network model based on node attraction with tunable parameters in order to solve the problems existing in BA model and the original node attraction model. The model considered the effects of preferential attachments by the changes of degree and node attraction in the evolution process of networks. Theory research and simulation analysis show that we can more flexible adjust the evolution process of network through adjusting model parameters, therefore make it more accord with the network topology and statistical characteristics of real-world networks.