A Grey Forecasting Model Based on BP Neural Network for Crude Oil Production and Consumption in China

Abstract

The crude oil demand is growing rapidly in China, driven by its rapid industrialization and motorization. China has already become the second-largest oil importer nation in the world, after the United States. The dynamic GM(1,1) model of grey theory is used to develop the dynamic GM(M,N) model to forecast the crude oil consumption and production in China. In order to improve the forecasting accuracy, the original GM(1,1) model is improved by using BP Neural Network technique. We analyze the data of the crude oil consumption and production from 1995 to 2008 in China, and forecast China's crude oil consumption and production by this Grey Neural Network forecasting model, which shows that the improved grey forecasting model is of more reliability and higher forecasting accuracy than the original GM (1,1). The forecasting results indicate that China's crude oil consumption and production will continue to increase rapidly in the period of 2009 to 2015.