SIAR: An Effective Model for Predicting Game Propagation
摘要
The COVID-19 pandemic has revitalized focus on predictive models, but scant research has been devoted to modeling game transmission, and current models are inadequate in this regard. To predict the spread of games within the population, this paper proposes the “addiction individuals”, a new group based on the three groups of the SIR model. We applied the SIAR model, designed based on differential equations, to predict game transmission within this population. The SIAR model was validated on an existing dataset and compared with the traditional SIR model, demonstrating its greater accuracy.