Monitoring and evaluation of air quality in Jinan based on machine learning random forest model

The present study focuses on the monitoring and evaluation of air quality in Jinan, and utilises the random forest algorithm to construct a prediction model. Employing data from the China Air Quality Online monitoring and analysis platform from 1 January 2021 to 11 January 2025, the performance of the model was evaluated through data pre-processing, model construction and parameter optimisation. The findings demonstrate that the random forest model effectively captures the evolving trend of the air quality index in Jinan, thereby providing a scientific foundation for urban air quality monitoring and management.