共同进化
计算机科学
节点(物理)
转化(遗传学)
流行病模型
传输(电信)
顶点(图论)
免疫
数学优化
理论计算机科学
数学
生态学
生物
物理
人口
生物化学
电信
人口学
图形
遗传学
社会学
抗原
基因
量子力学
作者
Hongyuan Diao,Fuzhong Nian
标识
DOI:10.1142/s021798492250107x
摘要
In this paper, a two-layer network on various immunization strategies in the post-epidemic era is constructed and an improved symbiotic evolutionary model of COVID-19 and information collaboration is proposed. The dynamic transformation probability is introduced to influence the virus information transmission coevolutionary process. The dynamic transformation probability is influenced by the immunization strategies and vertex characteristics. We quantify the effects of immunization strategy, node properties, global temperature, and collaborative information dissemination on new crown outbreaks. We simulated our model in a scale-free network to analyze the propagation. The evolutionary phenomenon of the network during propagation was investigated. We simulated the proven epidemic information coevolutionary model in a two-layer network, validated it with real data comparisons by proving that our proposed model fits the real situation.
科研通智能强力驱动
Strongly Powered by AbleSci AI