一种基于距离偏好连接的网络演化模型

A Network Evolution Model Based on Distance-Preference Connections

摘要: 考虑到现实网络的实际情况以及BA无标度网络模型不能展现真实网络的高聚类特性，本文提出了一个带调节参数的基于距离偏好连接的网络演化模型。通过仿真实验显示，模型的度分布不再遵循无标度分布，而是满足负指数分布，并且通过调节距离因素依赖程度参数的数值，可以调整网络模型的聚类系数，从而获得具有更高聚类性质的网络模型，更贴近真实网络的特征。

Abstract: Taking into account the actual situation of real networks and the inability of the BA scale-free network model to capture the high clustering characteristics of real networks, this paper proposes a distance-preference based network evolution model with a tunable parameter. Through simulation experiments, it is shown that the degree distribution of the model no longer follows a scale-free distribution, but instead follows a negative exponential distribution. By adjusting the value of the distance-preference dependence parameter, the clustering coefficient of the network model can be adjusted, thus obtaining a network model with higher clustering properties that is more closely aligned with the characteristics of real networks.