海南师范大学学报（自然科学版）2025，Vol.38Issue(2)：238-243,6.DOI:10.12051/j.issn.1674-4942.2025.02.015
基于贝叶斯方法的海口空气质量等级预报模型
Forecast Model for Air Quality Level in Haikou Based on Bayesian Method
摘要
Abstract
Meteorological observation data,reanalysis data and air quality observation data in Haikou during 2019 to 2021 were used to analyze the distribution of meteorological factors under different air quality levels and establish a Bayesian model for air quality level forecasting with data in 2022 as a test set.The results showed that an atmosphere condition of low relative humidity,moderate northerly component,low total cloud cover,no precipitation,and suitable temperature could contribute to the raising of Haikou's air quality index(AQI).The Bayesian method had a good effect on air quality level forecasting,with an accuracy rate of 78.08%in test set.The first-level air quality was predicted with the best performance,followed by the second-level,and the third-level.The deviation of the model from the second and third levels was mainly due to higher vacancy rates,with a second-level of 42%and a third-level of 70%.However,the model had a lower false negative rate of only 10%for the third-level of air quality,indicating that this model could play a good role in the forecast-ing of air quality levels.关键词
空气质量等级预报/朴素贝叶斯方法/气温/北风分量Key words
air quality level forecast/Naive Bayes/temperature/north wind component分类
天文与地球科学引用本文复制引用
佟金鹤,刘丽君..基于贝叶斯方法的海口空气质量等级预报模型[J].海南师范大学学报（自然科学版）,2025,38(2):238-243,6.基金项目
海南省自然科学基金项目(421QN0967,422RC802) （421QN0967,422RC802）
