Complex Network Community Detection Algorithm And Disease Communication Research

The rise and development of the network science provide a new field for modeling and analysis of complex systems.The dynamics study of the information and disease in the network has a unique guiding role,which is conducive to reveal transmission mechanism and provide preventive strategies.The analysis of the network model is definitely not a copy of mathematical model,but relies on the analysis and detection of the topological structure.In return,a special network structure will also can simplify the analysis process.The community is one of the special network structures and can affect the transmission ways,such as its speed and route.Otherwise,the transmission is also affected by the adaptive behavior of individuals and the periodic switching of the network.There are some preliminary investigations about those problems and the main works are as follows:In chapter 1,we introduce the network complexity,its main research direction and the basic concepts.Besides,there are also some introductions about the definitions,detection methods and evaluation criterion of communities,and the related contents of Individual SIS model,the special structure of double networks and its periodic switching model.In chapter 2,we research the self-adaption switching algorithm based on the affinity propagation.Divided into two parts,the algorithm detects the strong and weak communities based on the single and double affinity of nodes.Through the numerical simulations,the algorithm accuracy is tested by the real network and the GN,LFR benchmark graph.Then we verify the robustness of the parameters.In chapter 3,based on the N-intertwined model,we build a SIS model in continuous time,then analyse the threshold condition and the stability of zero solution of linear system,which obtains the global stability of the nonlinear system.Through the numerical simulations,we study the effects of communities and the Individual local adaptation on the disease transmission.In chapter 4,we research the switching system in the double networks then obtain two conclusions.First,when the subsystems are all stable,the local stability of the zero solution of the switching system will not change with the length of the period and the dwell time.Second,we obtain the sufficient condition for local stability of switching systems when the stable and unstable subsystems coexist.Last,we test the effect of dwell time on the number of infected persons by numerical simulation,and provide effective prevention strategies for the initial stage of disease transmission.