Research On Computaional Model Of Natural Focus Diseases Based On Mutil-Agent And Complex Networks

The wide spread of natural focus diseases all over the world has become a serious public healthy and social problem. Now, natural focus diseases have begun to spread in the general population, posing a huge threat to human’s life. Thus, prevention and treatment of these diseases are extremely urgent and various studies on the transmission and control of natural focus diseases should be made to improve the prevention and treatment effect. Due to the limits of traditional simulation research methods on the disease propagation characteristics and the features that natural focus diseases are a type of infectious diseases, this paper proposes an improved scale-free networks infectious diseases’ spread model based on Multi-Agent and does research on the modeling techniques.First, this paper studies the basic characteristics of the individual Agent and two kinds of basic structural models of Agent, presenting a hybrid structural model of Agent suitable for infectious diseases’ spread by taking the advantages of these two models. Meanwhile, this paper analyses the internal structure of the components of Agent and studies FCM reasoning model applied to Agent decider. In addition, the individual Agent structural formalization model and its rules are defined in this paper. According to the infectious diseases’ spread mathematical model, this paper constructs the individual Agent status’ s transforming relationship in infectious diseases’ simulation model.Second, this paper studies construction algorithm of the small-world networks and scale-free networks based on complex networks theory, and studies the analytical method of the degree distribution and evolution mechanism of scale-free networks. Based on the fact that social network possesses small-world and scale-free property in the real world, the improved networks model not only has scale-free and small-world property, but also better meets the requirements of the simulation model by adding the internal edges, reconnecting edges and giving initial attraction to network nodes mechanism. In addition, both methods, theory and data simulation, verify that the improved networks model is a scale-free networks model.Finally, guided by theories of complex networks, using a bottom-up Multi-Agent simulation technology, this paper studies the individual behavior at the micro-level, social network interactive relationship at the macro-level and the co-evolution mechanism in the infectious diseases’ spread model. Based on the above research, this paper constructs a Multi-Agent and improved scale-free networks infectious diseases’ spread model and combines the infectious diseases’ simulation model with GIS platform to demonstrate the simulation results better by map real time rendering.