Prediction of SO2 Emission from Industrial Sector in Shanghai City based on Novel Discrete Grey Model.

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Bibliographic Details
Title:	Prediction of SO2 Emission from Industrial Sector in Shanghai City based on Novel Discrete Grey Model.
Authors:	Jiefang Liu^1,2 liujflOI@126.com, Yunrui Guo¹, Bingjun Li², Pumei Gao³, Jian Liu⁴, Wanqin Zhang¹, Mingjun Jiao¹
Source:	Journal of Grey System. 2017, Vol. 29 Issue 3, p26-35. 10p.
Subjects:	Prediction models, Gray forecasting model, Sulfur oxides, Greenhouse gas mitigation, Perturbation theory
Geographic Terms:	Shanghai (China)
Abstract:	In order to reduce the modeling errors of the discrete grey prediction model and increase the stability of the solution, this paper presents the fractional-order reverse accumulative discrete grey forecasting model(FORA-DGM (1,1) model). The perturbation bounds of the model was analyzed through the matrix perturbation theory. And it is proved that the FORA-DGM (1,1) model has the smaller perturbation bounds of solution than traditional discrete grey forecasting model. Thus, it has good stability. Finally, the FORA-DGM (1,1) mode was applied to predict the SO2 emission from industrial sector in Shanghai city. The modeling results show that the simulation error and prediction error of FORA-DGM (1,1) mode was less than traditional discrete grey forecasting mode, especially in the prediction aspects. And it verified the validity and practicability of the FORA-DGM (1,1) mode. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	In order to reduce the modeling errors of the discrete grey prediction model and increase the stability of the solution, this paper presents the fractional-order reverse accumulative discrete grey forecasting model(FORA-DGM (1,1) model). The perturbation bounds of the model was analyzed through the matrix perturbation theory. And it is proved that the FORA-DGM (1,1) model has the smaller perturbation bounds of solution than traditional discrete grey forecasting model. Thus, it has good stability. Finally, the FORA-DGM (1,1) mode was applied to predict the SO2 emission from industrial sector in Shanghai city. The modeling results show that the simulation error and prediction error of FORA-DGM (1,1) mode was less than traditional discrete grey forecasting mode, especially in the prediction aspects. And it verified the validity and practicability of the FORA-DGM (1,1) mode. [ABSTRACT FROM AUTHOR]
ISSN:	09573720