提出了复杂网络上一种基于再度感染的SIS传播模型.在具有树状分支结构的网络中,针对某个染病节点,在考虑其感染子节点的同时,也考查其再次感染祖先节点的情况.分别在小世界网络和无标度网络上进行仿真分析,结果表明,对于小世界网络,基于再度感染的SIS传播模型的稳态感染密度比传统的SIS传播模型的要大,而且感染周期越短,稳态感染密度越大;而对于无标度网络,虽然基于再度感染的SIS传播模型的稳态感染密度也比传统的SIS传播模型的要大,但是,感染周期对于稳态感染密度的影响微乎其微,甚至可以忽略.
A new SIS model based on reinfection in complex networks was proposed. By using the model in the network with a tree-like sturcture,not only the infection of descendants of an infected node was considered but also the reinfection of ancestor by the infected node was taken into ac count. Through theoretical analysis and numerical simulation on small-world networks and scalefree networks, it is found that: for small-world networks, the stationary infected density on this new model is larger than that on the traditional SIS model, and the shorter the infection time is, the gerater the stationary infected density will be;however for the scale-free networks, the stationary in fected density on this new model is still larger than that on the traditional SIS model, yet the effect of the infection time on the stationary infected density can be neglected.