System Development & Application
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1809-1814

Long-term prediction of PM2.5 concentration based on deep learning

Huang Weijian
Li Danyang
Huang Yuan
School of Information & Electrical Engineering, Hebei University of Engineering, Handan Hebei 056038, China
DOI: 10.19734/j.issn.1001-3695.2020.08.0254

Abstract

In order to improve the long-term prediction accuracy of PM2.5, this paper proposed a TSMN(time series memory network) prediction model based on deep learning by taking air pollutants and meteorological factors as the influencing factors. The model consisted of two components. The local memory component used external memory to improve the long-range memory capacity of the model, and cooperated with the neighborhood component that modeled the multi-site spatial relationship to complete long-term prediction of PM2.5 from the perspective of time and space. This paper compared the TSMN model with multiple models by using different evaluation indicators. Comparing the TSMN model with the better-performing CNN-LSTM model, the RMSE and MAE of this model goes down 5.2% and 5.7% respectively, and the R2 goes up 7.5%. The experimental results show that the TSMN model can effectively improve the long-term prediction accuracy of PM2.5 concentration.

Foundation Support

河北省自然科学基金资助项目(F2015402077)
河北省高等学校科学技术研究项目(QN2018073)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.08.0254
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: System Development & Application
Pages: 1809-1814
Serial Number: 1001-3695(2021)06-039-1809-06

Publish History

[2021-06-05] Printed Article

Cite This Article

黄伟建, 李丹阳, 黄远. 基于深度学习的PM2.5浓度长期预测 [J]. 计算机应用研究, 2021, 38 (6): 1809-1814. (Huang Weijian, Li Danyang, Huang Yuan. Long-term prediction of PM2.5 concentration based on deep learning [J]. Application Research of Computers, 2021, 38 (6): 1809-1814. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)