Paper Info
Title
Grey Prediction with Markov-Chain 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(l, I) model to forecast the crude oil consumption and production in China. In order to improve the forecast accuracy, the original GM (1, 1) models are improved by using Markov-chain. We analyze the data of the crude oil consumption and production from 1990 to 2006 in China, and forecast China's crude oil consumption and production by this Grey-Markov forecasting model, which shows that the improved grey forecasting model is of more reliability and higher forecast accuracy than GM (1, 1). The forecast results indicate that China's crude oil consumption and production will continue to increase rapidly in the period of 2007 to 2015.
Year
DOI
Venue
2009
10.1007/978-3-642-01216-7_58
SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009)
Keywords
Field
DocType
Grey system theory,Markov-chain,Grey forecasting model
Computer science,Markov chain,China,Crude oil,Artificial intelligence,Machine learning,Gray (horse),Agricultural engineering
Conference
Volume
ISSN
Citations 
56
1867-5662
1
PageRank 
References 
Authors
0.48
0
2
Name
Order
Citations
PageRank
Hongwei Ma110.48
Zhaotong Zhang220.82