The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast global oil consumption.
Simulated sequences will be generated randomly, and used to test the models included in the GM(1,1) model cluster; and these grey forecasting models are applied to forecast global oil consumption.
Effectiveness of these grey forecasting models is proved by random experiments, which explains the model adaptability. Global oil consumption is predicted, and it shows that global oil consumption will increase at a rather big growth rate in the next years.
The effectiveness of medium-term prediction of these grey forecasting models is analyzed by random experiments. These models are compared, and some basis for model selection is obtained.
The authors would like to thank for the constructive suggestions of the two anonymous reviewers. This work was supported by National Natural Science Foundation of China under Grant No. 71573120, the Fundamental Research Funds for the Central Universities under Grant No. NS2015084, Jiangsu Natural Science Fund under Grant No. BK20130785, Doctoral Fund of China Ministry of Education under Grant No. 20133218120036, Aviation Science Foundation under Grant No. 2014ZG52077.
Yuan, C., Zhu, Y., Chen, D., Liu, S. and Fang, Z. (2017), "Using the GM(1,1) model cluster to forecast global oil consumption", Grey Systems: Theory and Application, Vol. 7 No. 2, pp. 286-296. https://doi.org/10.1108/GS-01-2017-0001Download as .RIS
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