Modeling of Stochastic SIQR Infectious Disease Models and Optimal Control

In this paper, a novel SIQR infectious disease model is proposed, which takes into account the effects of isolation bins and media coverage on transmission, and introduces Brownian motion to describe the uncertainty in the system. Vaccination is added as an optimal control strategy in order to effectively control the infectious disease and reduce the cost. Since the nonlinear HJB equations are more complex and difficult to solve in continuous-time nonlinear systems subject to random perturbations, the online execution and judging neural network technique is used to solve the optimal control strategy more efficiently and accurately when the weighting parameters are dynamically adjusted according to the real-time data. Simulation examples verify that the method can effectively control the spread of infectious diseases.