摘要
在典型的SIRS模型的基础上,提出了一种无标度网络中带人工免疫的SIRS类传染病模型。运用平均场理论方法分析了所提模型的动力学行为,研究了在两种不同的人工免疫策略下病毒在一种特定的无标度网络上的传播情况,并模拟了两种免疫策略对病毒传播的影响。模拟结果表明,通过人工免疫可以有效降低稳态感染比例,提高系统的传播阈值,从而有效控制病毒在复杂网络上的传播。
The infectious SIRS model with artificial immunization was proposed based on SIRS model and scale-free na- ture on complex networks. The dynamic behavior of the model was studied through a mean-field theory. We studied the spreading of disease in the special scale-free networks through two different artificial immunization strategies, and simu- lated different impact of each strategy on disease spreading. The result shows that artificial immunization can effectively reduce infection rates and improve the system spreading threshold, so as to effectively eontrol the disease spreading on complex networks.
出处
《计算机科学》
CSCD
北大核心
2013年第6期211-214,共4页
Computer Science
基金
重庆市自然科学基金(CSCT,2010BA2003)资助
关键词
无标度网络
人工免疫
SIRS模型
免疫策略
Scale-free network, Artificial immunization, SIRS model, Immunization strategies