ConvFormer-KDE: A Long-Term Point-Interval Prediction Framework for PM2.5 Based on Multi-Source Spatial and Temporal Data Article

Lin, Shaofu, Zhang, Yuying, Fei, Xingjia et al. (2024). ConvFormer-KDE: A Long-Term Point-Interval Prediction Framework for PM2.5 Based on Multi-Source Spatial and Temporal Data . 12(8), 10.3390/toxics12080554

Open Access

cited authors

  • Lin, Shaofu; Zhang, Yuying; Fei, Xingjia; Liu, Xiliang; Mei, Qiang

sustainable development goals

authors

publication date

  • August 1, 2024

keywords

  • Environmental Sciences
  • Environmental Sciences & Ecology
  • Life Sciences & Biomedicine
  • Science & Technology
  • Toxicology
  • convolutional neural network
  • fine particulate matter
  • interval prediction
  • kernel density estimation
  • long-term point prediction
  • transformer

Digital Object Identifier (DOI)

publisher

  • MDPI

volume

  • 12

issue

  • 8