广义带有随机活化机制的钝化网络模型研究

Research on generalized deactivation network model with random activation mechanism

带有随机活化的钝化网络模型可以解释实证引文网络中有一些文章是在后期才被人们关注的现象,但是新进节点必须与当前的每个活跃态节点都连接的限定不能反映真实引文网络中的随机效应.文中提出了一种广义的带有随机活化机制的钝化网络模型,该模型考虑了新进节点可以从当前的活跃态节点中随机选取一定数量的节点建立连接的情况.利用该模型对网络整体的入度分布进行理论解析和数值模拟,得到了一致的结果.此外,三个实证科学引文网络的实证数据与该模型的数值模拟结果吻合较好.

The deactivation network model with random activation can explain the phenomenon that some articles in the empirical citation network are paid attention to in the later stage,but the restriction that the new node must be connected with every active node cannot reflect the random effect in the real citation network.In this paper,a generalized deactivation network model with random activation mechanism is proposed.The model considers that the new nodes can randomly select a certain number of nodes from the current active nodes to establish connections.The model is used to analyze and simulate the whole network input degree distribution,and the consistent results are obtained.In addition,the empirical data of the three empirical science citation networks are in good agreement with the numerical simulation results of this model.