Haze risk: information diffusion based on cellular automata

Negative effects of haze risk can easily spread faster and more widely, however, existing studies rarely investigate the whole period or cycle diffusion events, which leads to lowered public knowledge, often resulting in exaggerated negative effects. In this paper, simulation model based on cellular automata is used evaluate information. Firstly, according whole-life emergencies, affected by information classified resembling SEIR infectious disease model. Secondly, a rule from unknown exposed individuals developed theory automata. Then, individual state transformation at different stages, regarding propagation constructed. Finally, appropriate parameters are selected calculate results without intervention. The show that during evolution process, unknowns continue decrease, lurkers increase. Due existence immunization period, immunized persons reach their maximum number before they about lose immunity, communicators reaches minimum. Afterward, reduced stable level, continues increase toward an agglomeration benefit. Therefore, order achieve effective control information, strong weak measures taken for each type individuals, immunity increased control. For entire control, communicator reduce conversion rate. study helps public's sense responsibility, improve government's credibility, contributes establishment harmonious society.