The concentration of PM2. 5 is an important index to measure the degree of air pollution.
When it exceeds the standard value, it is considered to cause pollution and lower the air …

PM2. 5 is one of the most important pollutants related to air quality, and the increase of its
concentration will aggravate the threat to people's health. Therefore, the prediction of …

Air pollution is a growing problem and poses a challenge to people's healthy lives. Accurate
prediction of air pollutant concentrations is considered the key to air pollution warning and …

Air pollution has become a critical factor affecting the health of human beings. Forecasting
the trend of air pollutants will be of considerable help to public health, including improving …

Urban particulate matter forecasting is regarded as an essential issue for early warning and
control management of air pollution, especially fine particulate matter (PM2. 5). However …

As people focus more on environmental protection, air quality prediction plays an
increasingly important role in reducing pollution hazards. Both fine particulate matter (PM2 …

Aiming at the problems of low accuracy and less prediction time step in traditional statistical
model for PM2. 5 concentration prediction, a PM2. 5 concentration prediction method based …

Prolonged exposure to high concentrations of suspended particulate matter (SPM),
especially aerodynamic fine particulate matter that is≤ 2.5 μm in diameter (PM2. 5), can …

In order to improve the accuracy of PM2. 5 concentration forecast in Beijing Meteorological
Bureau, a deep learning prediction model based on convolutional neural network (CNN) …

The problem of air pollution has attracted more and more attention. PM2. 5 is a key factor
affecting air quality. In order to improve the prediction accuracy of PM2. 5 concentration and …