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摘要:
Considering dynamical disease spreading network consisting of moving individuals,a new double-layer network is constructed,one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves.On the basis of Markov chains theory,a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment.Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics.Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree.Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination.In addition,the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.
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智能网站Agents的研究
机器学习
智能Agents
信息系统
智能机器人的自适应自主Agents的建模
自主Agents
智能机器人
强化学习
凝视机制
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篇名 Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents
来源期刊 计算机、材料和连续体(英文) 学科 工学
关键词 Complex networks MARKOV CHAINS theory interaction process SPREADING dynamics DOUBLE-LAYER network
年,卷(期) 2018,(10) 所属期刊栏目
研究方向 页码范围 123-144
页数 22页 分类号 TP3
字数 语种
DOI
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研究主题发展历程
节点文献
Complex
networks
MARKOV
CHAINS
theory
interaction
process
SPREADING
dynamics
DOUBLE-LAYER
network
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
计算机、材料和连续体(英文)
月刊
1546-2218
江苏省南京市浦口区东大路2号东大科技园A
出版文献量(篇)
346
总下载数(次)
4
总被引数(次)
0
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