Predicting pm2.5 in the northeast china heavy industrial zone: a semi-supervised learning with spatiotemporal features

HIGHLIGHTS

  • who: Hongxun Jiang and collaborators from the School of Information, Renmin University of China, Beijing, China have published the paper: Predicting PM2.5 in the Northeast China Heavy Industrial Zone: A Semi-Supervised Learning with Spatiotemporal Features, in the Journal: Atmosphere 2022, 1744 of 26/03/2022
  • what: The authors provide support vector classification (SVC) to forecast the trend, i.e., an increase or a decrease in the PM2.5 index, in advance of time intervals of 1 h, 6 h, and 24 h. The authors 2.5 then constructed a vector,that and B . . .

     

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