As one of the main factors of air pollution,PM2.5 seriously affects human health,and attracts increasing attention of human beings.Scientific and efficient prediction of PM2.5 is conducive to human protection measures in advance to protect their own safety.In this paper,a prediction model of PM2.5 concentration based on time-domain convolutional neural network is de-signed,and the PM2.5 concentration in Xi'an city of Shaanxi province is predicted by selecting data from the real-time release platform of National Urban Air Quality of China Environmental Monitoring Station,and the prediction results are analyzed.Compared with the long and short memory neural network and gated cyclic unit model,the results show that the convolutional neural network has better performance in predicting PM2.5 concentration.
万方数据
