A Hybrid Deep Learning Model Based on LSTM for Long-term PM2.5 Prediction

被引:0
|
作者
Chen, Yibin [1 ]
Wu, Mingyang [1 ]
Tang, Ruiping [2 ]
Chen, Shuai [3 ]
Chen, Senbo [1 ]
机构
[1] School of Information and Technology, Nantong University, China
[2] School of Life Sciences, Nantong University, China
[3] School of Mechanical Engineering, Nantong University, China
关键词
CNN - Deep learning - Industrialisation - Learning models - LSTM - Model-based OPC - Multivariate data sets - Pm2.5 prediction - Univariate - Urgent problems;
D O I
暂无
中图分类号
学科分类号
摘要
24
引用
收藏
页码:55 / 60
相关论文
共 50 条
  • [21] Time series prediction of the chemical components of PM2.5 based on a deep learning model
    Liu K.
    Zhang Y.
    He H.
    Xiao H.
    Wang S.
    Zhang Y.
    Li H.
    Qian X.
    [J]. Chemosphere, 2023, 342
  • [22] Prediction of PM2.5 concentration based on the weighted RF-LSTM model
    Ding, Weifu
    Sun, Huihui
    [J]. EARTH SCIENCE INFORMATICS, 2023, 16 (04) : 3023 - 3037
  • [23] Prediction of PM2.5 concentration based on the weighted RF-LSTM model
    Weifu Ding
    Huihui Sun
    [J]. Earth Science Informatics, 2023, 16 : 3023 - 3037
  • [24] Improved Hourly and long-term PM2.5 Prediction Modeling Based on MODIS in Bangkok
    Kumharn, Wilawan
    Sudhibrabha, Sumridh
    Hanprasert, Kesrin
    Janjai, Serm
    Masiri, Itsara
    Buntoung, Sumaman
    Pattarapanitchai, Somjet
    Wattan, Rungrat
    Pilahome, Oradee
    Nissawan, Waichaya
    Jankondee, Yuttapichai
    [J]. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2022, 28
  • [25] An improvement of PM2.5 concentration prediction using optimised deep LSTM
    Choe T.-H.
    Ho C.-S.
    [J]. International Journal of Environment and Pollution, 2022, 69 (3-4) : 249 - 260
  • [26] Short-term prediction of PM2.5 pollution with deep learning methods
    Ayturan, Y. A.
    Ayturan, Z. C.
    Altun, H. O.
    Kongoli, C.
    Tuncez, F. D.
    Dursun, S.
    Ozturk, A.
    [J]. GLOBAL NEST JOURNAL, 2020, 22 (01): : 126 - 131
  • [27] An improvement of PM2.5 concentration prediction using optimised deep LSTM
    Choe, Tong-Hyok
    Ho, Chung-Song
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, 2021, 69 (3-4) : 249 - 260
  • [28] The application of strategy based on LSTM for the short-term prediction of PM2.5 in city
    Lin, Min -Der
    Liu, Ping-Yu
    Huang, Chi-Wei
    Lin, Yu-Hao
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 906
  • [29] A Deep Learning-Based Multi-objective Optimization Model for PM2.5 Prediction
    Wenkai Xu
    Fengchen Fu
    Qingqing Zhang
    Lei Wang
    [J]. International Journal of Computational Intelligence Systems, 16
  • [30] A Deep Learning-Based Multi-objective Optimization Model for PM2.5 Prediction
    Xu, Wenkai
    Fu, Fengchen
    Zhang, Qingqing
    Wang, Lei
    [J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2023, 16 (01)