Research On Air Quality Analysis And Prediction Method Based On Machine Learning

With the continuous development of social economy,people's living standards have been greatly improved,but environmental problems are becoming more and more serious,which has a lot of negative effects on people's quality of life.Because the influencing factors of air quality are complex,dynamic,changeable and complex,it is of great significance to effectively analyze the relationship between these influencing factors and air quality,and then to study the evolution law of air quality.In this context,this paper proposes a machine learning-based air quality modeling and analysis method,which fully takes into account the meteorological,environmental and other air quality related factors,in order to achieve an accurate analysis of the evolution trend of air quality.Firstly,the constraints affecting air quality are analyzed from two dimensions: meteorological characteristics and environmental characteristics.Meteorological characteristics are defined as local meteorological factors(i.e.temperature,rainfall,humidity,pressure,wind speed,wind direction),environmental characteristics are defined as internal factors(i.e.historical pollutant concentration in target area)and external factors(pollutant concentration in surrounding area).Secondly,the abstract air quality impact characteristics are concretized by qualitative and quantitative methods.The correlation between air quality and meteorological and environmental characteristics was qualitatively analyzed by numerical fitting method,and the coupling relationship between meteorological factors was quantitatively analyzed by Pearson correlation coefficient,and the characteristic values needed for air quality prediction were extracted.Thirdly,an air quality analysis and prediction model based on machine learning is proposed.On the basis of the correlation analysis of meteorological characteristics,a Bayesian network analysis and prediction method is proposed.On the basis of the correlation analysis of environmental characteristics,a random forest analysis and prediction method is proposed.Finally,based on the above analysis results,a collaborative prediction model of air quality is established to achieve accurate prediction of air quality.Finally,the prediction results of the model proposed in this paper are analyzed.Through the prediction of air quality at future time,the comparative analysis results show that the model proposed in this paper considers more comprehensive factors,and the prediction accuracy is higher than that of the traditional single prediction model.And the specific relationship between the influencing factors of air quality is analyzed by charts.