Research on Air Quality of Beijing-Tianjin-Hebei Region based on SVM and Regression Analysis

DOI

10.2991/iceemr-17.2017.82How to use a DOI?

Keywords

support vector machine (SVM), data mining, multivariate linear regression, air quality index (AQI)

Abstract

The air pollution of Beijing-Tianjin-Hebei region in China becomes increasingly serious. Focus on the air quality management of Beijing-Tianjin-Hebei region, this paper proposes a method based on SVM algorithm and multivariate linear regression to the prediction and evaluation of air quality. First, it builds the evaluation metrics based on the weather factors, the correlation of neighbor cities, and their combination. Furthermore, it applies the SVM algorithm to the classification and prediction of air quality of Beijing-Tianjin-Hebei region. By the application of multivariate linear regression method, the weather factor with no significant effect on air quality is removed to save the cost of calculation. Finally, the experimental results show that the method based on the combination of weather factors and correlation of neighbor cities is better than the other two methods. We draw the conclusion that the method is feasible and effective.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li Tang
AU  - Caiyun Zhou
AU  - Li He
AU  - Shuhua Zhang
PY  - 2017/05
DA  - 2017/05
TI  - Research on Air Quality of Beijing-Tianjin-Hebei Region based on SVM and Regression Analysis
BT  - Proceedings of the 2017 International Conference on Education, Economics and Management Research (ICEEMR 2017)
PB  - Atlantis Press
SP  - 327
EP  - 330
SN  - 2352-5398
UR  - https://doi.org/10.2991/iceemr-17.2017.82
DO  - 10.2991/iceemr-17.2017.82
ID  - Tang2017/05
ER  -