DocumentCode :
1658937
Title :
A Grey Forecasting Model Based on BP Neural Network for Crude Oil Production and Consumption in China
Author :
Ma, Hongwei ; Wu, Yonghe
Author_Institution :
Coll. of Eng., Nanjing Agric. Univ., Nanjing, China
fYear :
2010
Firstpage :
105
Lastpage :
109
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.
Keywords :
backpropagation; crude oil; grey systems; neural nets; production engineering computing; BP neural network; backpropagation; crude oil consumption; crude oil production; grey forecasting model; Artificial neural networks; Biological system modeling; Forecasting; Mathematical model; Petroleum; Predictive models; Production; BP Neural Network; crude oil production; grey theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Processing (ISIP), 2010 Third International Symposium on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-8627-4
Type :
conf
DOI :
10.1109/ISIP.2010.12
Filename :
5669010
Link To Document :
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