Thumbnail
Access Restriction
Open

Author Wang, Xiaoyu ♦ Luo, Dongkun ♦ Liu, Jianye ♦ Wang, Wenhuan ♦ Jie, Guixin
Editor Strelniker, Yakov
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2017
Language English
Abstract The accurate and reasonable prediction of natural gas consumption is significant for the government to formulate energy planning. To this end, we use the multiverse optimizer (MVO) algorithm to optimize the parameters of the Nash nonlinear grey Bernoulli model (NNGBM (1,1)) and propose a hybrid MVO-NNGBM model to predict the natural gas consumption in 30 regions of China. The results indicate that the prediction precision of the hybrid MVO-NNGBM model is better than that of other grey-based models. According to the forecast results, China’s natural gas consumption will grow rapidly over the next five years and reach 354.1 billion cubic meters (bcm) by 2020. Moreover, the spatial distribution of natural gas consumption will shift from being supply oriented towards being demand driven and will be mainly concentrated in coastal and developed provinces.
ISSN 1024123X
Learning Resource Type Article
Publisher Date 2017-11-15
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 15635147
Journal Mathematical Problems in Engineering
Volume Number 2017
Page Count 10


Open content in new tab

   Open content in new tab