首页|Chinese Academy of Sciences Researcher Targets Machine Learning (Estimation of PM2.5 Concentration across China Based on MultiSource Remote Sensing Data and Machine Learning Methods)
Chinese Academy of Sciences Researcher Targets Machine Learning (Estimation of PM2.5 Concentration across China Based on MultiSource Remote Sensing Data and Machine Learning Methods)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Mdpi
A new study on artificial intelligence is now available. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Long-term exposure to high concentrations of fine particles can cause irreversible damage to people’s health.” Funders for this research include Forestry Technological Developments And Monitoring And Assessment of Terrestrial Ecosystem Research. The news reporters obtained a quote from the research from Chinese Academy of Sciences: “Therefore, it is of extreme significance to conduct large-scale continuous spatial fine particulate matter (PM2.5) concentration prediction for air pollution prevention and control in China. The distribution of PM2.5 ground monitoring stations in China is uneven with a larger number of stations in southeastern China, while the number of ground monitoring sites is also insufficient for air quality control. Remote sensing technology can obtain information quickly and macroscopically. Therefore, it is possible to predict PM2.5 concentration based on multi-source remote sensing data. Our study took China as the research area, using the Pearson correlation coefficient and GeoDetector to select auxiliary variables. In addition, a long shortterm memory neural network and random forest regression model were established for PM2.5 concentration estimation.”
NETL
NSTL
Mdpi
