现代信息科技2025，Vol.9Issue(10)：17-22,6.DOI:10.19850/j.cnki.2096-4706.2025.10.005
基于机器学习的城市空气质量预测模型分析
Analysis of Urban Air Quality Prediction Model Based on Machine Learning
摘要
Abstract
This paper studies and analyzes prediction models based on different Machine Learning methods aiming to improve the accuracy of urban air quality prediction.Taking the air quality of Guangzhou in 2018 as an example,firstly,the correlation between urban air quality and its characteristics is analyzed through time series and correlation research.Then,based on Random Forest regression,Decision Tree regression and Gradient Boosting Tree algorithm respectively,AQI prediction models are constructed to determine the better model.Finally,the model is optimized by grid search for parameter tuning.The results show that the best prediction model is based on Random Forest regression,with a RMSE of 8.93 and a goodness of fit of 0.88.It has strong prediction accuracy and can effectively predict the urban air quality index.关键词
城市空气质量/机器学习/网格搜索/预测模型Key words
urban air quality/Machine Learning/grid search/prediction model分类
信息技术与安全科学引用本文复制引用
朱效锋,张倩,朱小平..基于机器学习的城市空气质量预测模型分析[J].现代信息科技,2025,9(10):17-22,6.基金项目
辽宁省科技计划联合基金项目(2023-MSLH-256) （2023-MSLH-256）
