Research on PM2.5 concentration prediction algorithm based on graph convolutional neural network model

被引:0
|
作者
Liu, Xiangyu [1 ]
Ren, Ge [2 ]
Guo, Jiashuo [1 ]
Hu, Yuxin [2 ]
Lin, Hong [2 ]
机构
[1] School of Computer Science and Artificial Intelligence, Zhengzhou University, Zhengzhou, China
[2] Zhengzhou Institute of Metrology, Zhengzhou, China
关键词
Concentration prediction - Convolutional networks - Convolutional neural network - Deep learning - Graph neural networks - Monitoring stations - PM2.5 concentration - Pm2.5 concentration prediction - Prediction modelling - Traffic emissions;
D O I
132916J
中图分类号
学科分类号
摘要
12
引用
收藏
相关论文
共 50 条
  • [31] A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory
    Qi, Yanlin
    Li, Qi
    Karimian, Hamed
    Liu, Di
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 664 : 1 - 10
  • [32] Application of TCN-biGRU neural network in PM2.5 concentration prediction
    Shi, Ting
    Li, Pengyu
    Yang, Wu
    Qi, Ailin
    Qiao, Junfei
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (56) : 119506 - 119517
  • [33] The Prediction of PM2.5 Value Based on ARMA and Improved BP Neural Network Model
    Zhu, Hongxia
    Lu, Xiuhua
    2016 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS (INCOS), 2016, : 515 - 517
  • [34] Forecasting PM2.5 Concentration in India Using a Cluster Based Hybrid Graph Neural Network Approach
    Pavan Sai Santhosh Ejurothu
    Subhojit Mandal
    Mainak Thakur
    Asia-Pacific Journal of Atmospheric Sciences, 2023, 59 : 545 - 561
  • [35] Forecasting PM2.5 Concentration in India Using a Cluster Based Hybrid Graph Neural Network Approach
    Ejurothu, Pavan Sai Santhosh
    Mandal, Subhojit
    Thakur, Mainak
    ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2023, 59 (05) : 545 - 561
  • [36] Prediction of PM2.5 based on Elman neural network with chaos theory
    Hu Zhiqiang
    Li Wenjing
    Qiao Junfei
    PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 3573 - 3578
  • [37] Study on prediction of atmospheric PM2.5 based on RBF neural network
    Zheng Haiming
    Shang Xiaoxiao
    2013 FOURTH INTERNATIONAL CONFERENCE ON DIGITAL MANUFACTURING AND AUTOMATION (ICDMA), 2013, : 1287 - 1289
  • [38] Classification prediction model of indoor PM2.5 concentration using CatBoost algorithm
    Guo, Zhenwei
    Wang, Xinyu
    Ge, Liang
    FRONTIERS IN BUILT ENVIRONMENT, 2023, 9
  • [39] Development of a monthly PM2.5 forecast model for Seoul, Korea, based on the dynamic climate forecast and a convolutional neural network algorithm
    Park, Ingyu
    Ho, Chang-Hoi
    Kim, Jinwon
    Kim, Joo-Hong
    Jun, Sang-Yoon
    ATMOSPHERIC RESEARCH, 2024, 309
  • [40] Prediction of PM2.5 Concentration Based on NDFA-LSSVM Model
    Li, Jiangeng
    Shen, Jianing
    Li, Xiaoli
    2018 CHINESE AUTOMATION CONGRESS (CAC), 2018, : 3492 - 3497