Gray Prediction of Air Pollutants in Beijing Based on Improved Residual GM (1, 1) Model

DOI

10.2991/icmmita-16.2016.41How to use a DOI?

Keywords

air quality; Gray prediction; improved residual model; residual correction.

Abstract

Based on the gray system theory, the original gray predicting model, the residual correction model and the residual model have been established for PM10, SO2 and NO2, which are the major atmospheric pollution factors in Beijing. After comparing those three models, this paper established a new improved residual model, and the results show that: the improved residual model has reached a better accuracy in forecasting. This model can be used to predict the concentration of common pollutants in air in Beijing for the next few years as well as to forecast the development of air pollutants.

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  - Yong Shao
AU  - Yang Zhang
AU  - Changshun Yan
PY  - 2017/01
DA  - 2017/01
TI  - Gray Prediction of Air Pollutants in Beijing Based on Improved Residual GM (1, 1) Model
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 227
EP  - 233
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.41
DO  - 10.2991/icmmita-16.2016.41
ID  - Shao2017/01
ER  -