一种混合网络演化模型

结合Barabasi和Albert无标度网络模型和局域世界演化网络模型，提出了一种介于两种模型之间的混合网络模型．网络作为系统拓扑结构的描述；节点表示系统元素，边则表示元素之间的相互作用．在该模型的增长过程中，每一个时间步进入网络的节点都基于各自的内在性质或外部条件，在局域世界或全局范围内与网络中已存在的节点择优连接，从而产生一种具有不同局部拓扑结构的网络．通过调整参数P可以在Barabasi和Albert无标度网络模型和局域世界演化网络模型之间自由变换．仿真表明，该模型在保持Barabasi和Albert无标度网络模型和局域世界演化网络模型对随机故障鲁棒性的同时改善了它们对蓄意攻击的脆弱性．

A Hybrid Evolving Network Model

Based on the Barabasi-Albert scale-free network model and the local-world evolving network model, a hybrid network model is proposed, which is between the two models. Networks can be used to describe the topology systems, in which the nodes represent the system elements and the edges represent the interactions between them. During the growing process of this hybrid model, the nodes added in every time-step are based on their own internal characteristics or external conditions, and optimally connect with the pre-existing nodes in either the local or global preferences, thus creating a network with different local topologies. By adjusting the parameter p, the model can be freely transformed between the Barabasi-Albert scale-free network model and the local-world evolving network model. Simulations indicate that the proposed hybrid model can no only maintain the network robustness of the Barabasi-Al- bert scale-free network model and the local-world evolving network mode, but reduce their fragility against intentional attacks as well.