Study On Threshold Problem Of Time Series Network Based On SIR Disease Propagation Model

The temporal network is based on the static network and considers the time fac-tor,using temporal network to study information or disease spreading in network can more effectively reflect the characteristics of disease diffusion in network.The research on the diffusion behavior of disease in complex networks is generally based on the clas-sical SIR disease spreading model,all nodes in the model have the same probability of infection,In the actual network,when the disease is spread between individuals,different individuals have different resistance to diseases.Different resistance abilities arc manifested in different physical strength,different disease resistance and so on,The difference between the individual and the individual is not well represented in the SIR disease diffusion model,but only the probability that each node has the same infectious disease.In this article,we further study the SIR disease diffusion model and find a better way to express the differences of the nodes in the spread of disease.In this article,each node is given a random value in the[0,1]interval.This value represents the adaptive ability of the node(infection ability),in course of disease spreading,only when the adaptive ability of the susceptible node is greater than the adaptive ability of the infected node,the susceptible node can be infected.This method is applied to two networks,the results show that the greater the adaptive ability of the node,the greater the infection ability of the node,the results show that in the spread of disease,the more infected nodes,the greater the ability to spreading disease.Finally,the number of nodes infected with disease in the network is higher.In the complex network,the research on information spreading behavior is ma-ture and the number of infected nodes affected by nodal infection.There are many related models and the linear threshold model is applied in this paper.The most im-portant feature of the model is its value accumulation characteristics.In this paper,the value accumulation characteristics of the model are applied to the disease propa-gation model.In the spread of disease,the number of infected nodes affected by nodal infection is affected.In this paper,the influence of infected nodes on susceptible n-odes can be accumulated when the infected nodes are exposed to infected nodes.The results showed that the more nodes infected neighbors,the more likely the node was to be infected.Secondly,according to the characteristics of disease transmission in actual network,This paper explores the relationship between the infection ability of nodes in the network and the time window size and disease spreading probability.