广东工业大学学报 ›› 2018, Vol. 35 ›› Issue (05): 51-59.doi: 10.12052/gdutxb.180058

• 综合研究 • 上一篇    下一篇

多因素制约下的SIR传染病模型的元胞自动机仿真模拟研究

郑三强, 韩晓卓   

  1. 广东工业大学 应用数学学院, 广东 广州 510520
  • 收稿日期:2018-03-22 出版日期:2018-07-10 发布日期:2018-07-18
  • 通信作者: 韩晓卓(1978-),女,副教授,主要研究方向为生物数学.E-mail:hanxzh@gdut.edu.cn E-mail:hanxzh@gdut.edu.cn
  • 作者简介:郑三强(1993-),男,硕士研究生,主要研究方向为生物数学.
  • 基金资助:
    国家自然科学基金资助项目（31670391）

A Simulation of Cellular Automata Based on the SIR Infectious Disease Model with Multifactorial Constraints

Zheng San-qiang, Han Xiao-zhuo   

  1. School of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520, China
  • Received:2018-03-22 Online:2018-07-10 Published:2018-07-18

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摘要： 针对多因素传染病的精确仿真，根据非高斯传染模型下模拟感染者的随机游走行为，通过构造传染病中心疫区的高斯压力死亡模型，采用基于sigmoid函数的痊愈率与不同隔离强度模拟感染者个体的被动转化行为，且其行为的发生服从动态泊松概率，建立了一类多因素制约下的元胞自动机传染病模型.通过对比实验发现，该模型的模拟仿真稳定，且能较精确仿真疫病传播的实际情况，相比目前的模型具有更高的精度.

关键词: 元胞自动机, 传染病模型, 高斯非邻体传染, 高斯压力, sigmoid函数

Abstract: Aiming at accurate simulation of multifactor infectious diseases and using Gauss-pressure model to simulate death in a central epidemic area, using the recovery rate and isolation intensity based on the sigmoid function to simulate the passive transformation of the infected individual, with the probability of the occurrence of its behavior obeying the dynamic probability, a multi-factor cellular automata infections disease model is established. Some comparison experiments are carried out on the model, and the results show that the model is more stable and more able than the current model to accurately simulate the actual situation of epidemic disease transmission.

Key words: cellular automata, epidemic model, Gaussian non-neighborhood infection, Gauss-pressure, sigmoid function

中图分类号: 

  • TP301.1
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