Air quality forecasting using SVR with quasi-linear kernel

Huilin Zhu, Jinglu Hu

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Air pollution has threaten people's health. It is urgent for the government to strengthen and enhance air pollution monitoring capacity. In this paper, we propose an air quality prediction model to infer air pollutant concentrations, such as CO, NOx, NO2. The idea is to design a sophisticate piecewise linear model by using a gated linear network. A top k% winner-take-all autoencoder is first built to generate a set of binary sequences as the gate control signals, so as to perform the input space partitioning. The piecewise linear model is then identified in an exact same way as a standard support vector regression (SVR) with a quasi-linear kernel composed by using the gate control signals. Results of our experiments shows that our proposed SVR prediction model outperforms other state-of-the-art methods.

本文言語English
ホスト出版物のタイトルCITS 2019 - Proceeding of the 2019 International Conference on Computer, Information and Telecommunication Systems
編集者Mohammad S. Obaidat, Zhenqiang Mi, Kuei-Fang Hsiao, Petros Nicopolitidis, Daniel Cascado-Caballero
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538640883
DOI
出版ステータスPublished - 2019 8
イベント2019 International Conference on Computer, Information and Telecommunication Systems, CITS 2019 - Beijing, China
継続期間: 2019 8 282019 8 31

出版物シリーズ

名前CITS 2019 - Proceeding of the 2019 International Conference on Computer, Information and Telecommunication Systems

Conference

Conference2019 International Conference on Computer, Information and Telecommunication Systems, CITS 2019
CountryChina
CityBeijing
Period19/8/2819/8/31

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Hardware and Architecture

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