forecasting natural gas production and consumption using grey model with latent information function: the cases of china and usa

The aim of the paper is to develop a grey model for short term forecasting of natural gas consumption and production in china and usa respectively. to enhance its prediction accuracy, the outliers are found by the error of the latent information function, and then corrected according to the test sample and the future trend. the sequence with corrected outliers is used to construct a grey model. the proposed model is employed to predict the natural gas consumption and production in china and usa. the results have demonstrated that the proposed model can raise the forecast accuracy of the grey model, and it also indicates that china will inevitably face a massive expansion in natural gas imports.