In order to scientifically construct the air quality monitoring system and improve the accuracy of air quality pre-diction,based on the uncertainty of massive monitoring data,the method based on Bayesian networks is proposed to predict the air quality index AQI and the corresponding level.This paper takes Hefei city as the research object.Firstly,the naive Bayesian classi-fication algorithm is used to predict the air quality level,and the classification accuracy of the tested samples obtained through train-ing is 85%.Because the conditional independence assumption of the algorithm is too strict,the Bayesian network model is further introduced for empirical study,and the prediction results are obtained based on the posterior probability distribution.The simulation experiment shows that the average absolute percentage error of AQI prediction for the tested samples is6.89%,and the accuracy of air quality grade classification is 90.28%.This indicates that Bayesian networks have good prediction performance,which can pro-vide technical support for air quality prediction and help the improvement of urban air quality.
关键词
空气质量等级/空气质量指数/朴素贝叶斯/贝叶斯网络/后验概率
Key words
air quality level/air quality index/naive Bayes/Bayesian Network/posterior probability
维普
万方数据