Title: Prediction of demand trends of coking coal in China based on grey linear regression composition model

Authors: Hai-Dong Zhou; Qiang Wu; Min Fang; Zhong-Bao Ren; Li-Fei Jin

Addresses: Institute of Industrial Economics of Land and Resources, Chinese Academy of Land and Resource Economics, P.O. Box 259, 101149 Beijing, China ' The Personnel Department, Chinese Academy of Land and Resource Economics, 101149, P.O. Box 259, Beijing, China ' Institute of Industrial Economics of Land and Resources, Chinese Academy of Land and Resource Economics, 101149, P.O. Box 259, Beijing, China ' School of Earth Sciences and Resources, University of Geosciences, 100083 Xueyuan Road 29, Haidian District City, Beijing, China ' Institute of Land and Resources Planning, Chinese Academy of Land and Resource Economics, 101149, P.O. Box 259, Beijing, China

Abstract: The scarce of coking coal resources in China results in its short supply. By establishing a grey linear regression composition model, this paper has greatly improved the inadequacy of grey system prediction model and regression analysis method in trend prediction and finished the prediction of demand trends of coking coal in China with this model. As result of the prediction, it is estimated that in the next decade, the demand for coking coal in China will experience a growth trend; China's demand for coking coal will reach more than 1.535 billion tons by 2015, reach the maximum of 1.639 billion tons by 2020 and drop in 2025.

Keywords: coking coal; grey linear regression composition model; linear regression modelling; residual test; global energy; China; coal demand.

DOI: 10.1504/IJGEI.2013.061794

International Journal of Global Energy Issues, 2013 Vol.36 No.2/3/4, pp.197 - 209

Received: 15 Oct 2012
Accepted: 02 Aug 2013

Published online: 12 Jul 2014 *

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