...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Mathematical Modelling >Global stability of deterministic and stochastic multigroup SEIQR models in computer network
【24h】

Global stability of deterministic and stochastic multigroup SEIQR models in computer network

机译：网络中确定性随机多组SEIQR模型的全局稳定性

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, we discuss multigroup SEIQR (susceptible, exposed, infectious, quarantined, and recovered) models with and without random perturbation in computer network. The transmission of malicious objects in computer network is formulated in these two models. In the deterministic model, the basic reproduction number R_0 is a threshold which completely determines the persistence or extinction of the disease. Using the results of the graph theory, we show if R_0 ＞ 1 , the disease will prevail, the infected fraction persists and the endemic equilibrium is globally stable in feasible region, if R_0 ≤ 1, the infected fraction of the nodes disappear so the disease die out. For the stochastic version, we carry out a detailed analysis on the asymptotic behavior of the stochastic model, also regarding of the value of R_0. When R_0 ＞ 1, we deduce the globally asymptotic stability of the endemic equilibrium by measuring the difference between the solution and the endemic equilibrium of the deterministic model in time average. Numerical methods are employed to illustrate the dynamic behavior of the model and simulate the system of equations developed. The effect of quarantine on recovered nodes is also analyzed in the deterministic model and the stochastic version of the determinist model.
机译：在本文中，我们讨论了计算机网络中带有或不带有随机扰动的多组SEIQR（易感，暴露，传染性，隔离和恢复）模型。这两种模型阐述了计算机网络中恶意对象的传播。在确定性模型中，基本繁殖数R_0是一个阈值，可以完全确定疾病的持久性或灭绝性。使用图论的结果，我们表明如果R_0＞ 1，疾病将流行，感染分数持续存在，并且在可行区域内流行平衡是整体稳定的，如果R_0≤1，则淋巴结的感染分数消失，因此疾病消亡。对于随机版本，我们对随机模型的渐近行为进行了详细分析，同时也考虑了R_0的值。当R_0＞ 1时，我们通过测量确定性模型在时间平均中的解与地方性均衡之间的差异，来推导地方性均衡的全局渐近稳定性。采用数值方法来说明模型的动态行为，并模拟所开发的方程组。在确定性模型和确定性模型的随机版本中，还分析了隔离对恢复节点的影响。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号