Forecasting Natural Gas Consumption of China Using a Novel Grey Model
Forecasting Natural Gas Consumption of China Using a Novel Grey Model
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DOI：
10.1155/2020/3257328
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
Chengli Zheng;Wen-ze Wu;Jianming Jiang;Qi Li
中科院分区：
文献类型：
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作者：
Chengli Zheng;Wen-ze Wu;Jianming Jiang;Qi Li
天然气消费量在我国能源市场中占有极其重要的地位，为了准确预测天然气消费量，本文在优化非齐次灰色模型（ONGM（1，1））的基础上，提出了一种新的灰色模型。首先利用行列式的乘积理论证明了预测结果与原始序列的首项无关，在此基础上，提出了在原始序列的首项前插入任意一个数字来提取信息的可靠方法，并在早期文献中证明了这是提高传统灰色模型预测精度的一种可行方法。通过一个在灰色模型预测精度检验中经常出现的实例验证了该模型的有效性，数值结果表明，该模型比其他常用的灰色模型具有更好的预测性能。最后，应用该模型对2019 - 2023年中国天然气消费量进行了预测，以期为能源部门和相关企业提供有价值的信息。
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.