The SEIR Dynamic Evolutionary Model with Markov Chains in Hyper Networks

In real life, individuals play an important role in the social networking system. When epidemic breaks out individual’s recovery rate depends heavily on network which he or she lives. For this reason, paper a nonlinear coupling dynamic model hyper was built. The upper layer is under hypernetwork vision, and lower physical contact layer. Thus, evolutionary mechanism between transmission established. At same time, deduced evolution process of system according to Markov chain method. probability equation determined, threshold spread non-uniform obtained. addition, numerical simulations verified correctness theory validity model. results show that state will be affected by ability degree information forgetting. Finally, suitable countermeasures are suggested suppress pandemic from spreading response model’s affecting factors.