Forecasting Natural Gas Consumption of China Using a Novel Grey Model

Author:

Zheng Chengli1ORCID,Wu Wen-Ze1ORCID,Jiang Jianming2ORCID,Li Qi1

Affiliation:

1. School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China

2. School of Mathematics and Statistics, Baise University, Baise 533000, China

Abstract

As is known, natural gas consumption has been acted as an extremely important role in energy market of China, and this paper is to present a novel grey model which is based on the optimized nonhomogeneous grey model (ONGM (1,1)) in order to accurately predict natural gas consumption. This study begins with proving that prediction results are independent of the first entry of original series using the product theory of determinant; on this basis, it is a reliable approach by inserting an arbitrary number in front of the first entry of original series to extract messages, which has been proved that it is an appreciable approach to increase prediction accuracy of the traditional grey model in the earlier literature. An empirical example often appeared in testing for prediction accuracy of the grey model is utilized to demonstrate the effectiveness of the proposed model; the numerical results indicate that the proposed model has a better prediction performance than other commonly used grey models. Finally, the proposed model is applied to predict China’s natural gas consumption from 2019 to 2023 in order to provide some valuable information for energy sectors and related enterprises.

Funder

Ministry of Education of the People's Republic of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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