Predicting PM2.5 Value in Future

Abstract

PM2.5 is a critical environmental issue, with high levels harming human health and the environment. Predicting PM2.5 levels can help implement preventive measures. This paper uses data mining techniques to address two problems: predicting the PM2.5 value for the next time session and determining the PM2.5 pollution level category for the next day. Neural networks and other models are used, showing good experimental results. The paper concludes with potential refinements to the prediction process.