Research On Modeling And Simulation Of Natural Focus Diseases Based On Complex Network

The wide spread of natural focus diseases has become a serious public healthy and social problem. The disease can be a serious threat to life. In addition, the transmission of the diseases caused by the virus has the potential to cause social panic and disturbance, while the cost of resources to prevent, control and treatment the disease. Because it is not possible to have experiments in the real world, so we must simulate. This paper studied traditional virus propagation simulation models, found that they are not very good to describe the reality. In view of the above reasons, an effective method is proposed to describe the characteristics and dynamics of virus transmission. The virtual network generated by the computer to mirror the complexity of the interaction between the real world and the dynamic process of virus transmission, and integrated with complex network. On this basis, to predict the development trend of infectious diseases, to prvide decision-making support for the development of public health measures through the analysis of the simulation results.In order to describe the real world in the simulation, the modeling method of traditional complex network virus propagation is studied. Test the similarities and differences between different complex networks and real networks by using the network characteristic value. Through experiments, it is found that the real world network is different from the regular network, the ER network and the BA network. WS network although has the double characteristics of small world, and high clustering coefficient, but it transfers a large amount of information, and has low failure rate, especially in the distributed environment. Based on this reason, a modified small world network model is proposed, which makes the amount of information exchanged limit to 2.5(7)2)9))2 level, and failure rate is reduced to 10%.In order to simulate the spread and the resistance of the virus spread, the mathematical model of virus transmission and effect of artificial immunity on the virus transmission were studied. Through the analysis, it is found that the SIS, SIR and SIRS model are not in conformity with the transmission of the virus in the real world. Therefore, based on the three mathematical models, the mathematical model of SIRSD virus propagation is proposed. The combination of the SIRSD model and artificial immune system is more authenticity.In order to show individual differences of Agent in the simulation, the formal description is studied. It is found that it is difficult to establish the corresponding logical expressions for some complex environmental states or beliefs, will, and so on. These concepts cannot be quantified in a computer. In order to solve this problem, an Agent model based on FCM is proposed. Through this model, the process of reasoning and the decision making process of avoiding infectious deseases can be well simulated.Based on the aforementioned studies, a simulation system of epidemic spreading is designed and implemented, and making it intergrated with the complex network. Next, the example of SARS virus transmission is simulated. After the analysis of the simulation results, the public health recommendations to control the spread of SARS are given.