基于邻节点总度数与随机区分度的无标度网络模型研究

Scale Free Network Model Based on Total Degree of Adjacent Nodes and Random Division

运用复杂网络基础知识,基于BA无标度网络模型构造方法,参考随机初始吸引度网络的优点与不足,提出了一种改进的无标度网络演化模型。该模型以节点区分度代替随机初始吸引度,使旧节点对于新节点的单方面吸引转变为两节点间的相互作用,更突出了不同节点间的差异性;考虑节点的实际影响力,以邻节点总度数作为择优连接标准,避免忽视潜在的重要节点,使网络更符合现实情况。通过实验仿真与分析,验证了该模型服从幂律分布,初始区分度对网络演化具有重要影响,且模型具有更小的邻节点总度数,网络的"贫富悬殊"程度降低,可以模拟更复杂的现实情况。

Based on the construction method of BA scale-free network model,this paper uses the basic knowledge of complex network and considers the advantages and disadvantages of random initial attraction network to propose an improved scale free network evolution model.In this model,the initial attraction degree is replaced by the division degree,then the old node＇s unilateral attraction to the new node is transformed into the interaction between the two nodes,which makes the differences between nodes more prominent;it also considers the actual influence of nodes and uses the total degree of neighbor node as the standard of preferential attachment,which avoids the negligence of potential important nodes,and makes the network more realistic.Through simulation and analysis,it verifies the model follows power-law distribution and the initial discrimination has important influence on the network evolution,and the model has a smaller total degree of nodes,the gap of the network between the rich and the poor decreases,it can simulate more complex reality.