Gray Prediction of Air Pollutants in Beijing Based on Improved Residual GM (1, 1) Model
Yong Shao, Yang Zhang, Changshun Yan
Available Online January 2017.
- https://doi.org/10.2991/icmmita-16.2016.41How to use a DOI?
- air quality; Gray prediction; improved residual model; residual correction.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/icmmita-16.2016.41 ID - Shao2017/01 ER -