Study on natural gas demand prediction model in China

被引：0

作者：

Feng, Xue ^{[1
]}

Zhang, Jinsuo ^{[1
]}

Zou, Shaohui ^{[1
]}

Bao, Wuyunbilige ^{[1
]}

机构：

[1] Xian Univ Sci & Technol, Xian 710054, Shaanxi, Peoples R China

来源：

SUSTAINABLE DEVELOPMENT OF INDUSTRY AND ECONOMY, PTS 1 AND 2 | 2014年 / 869-870卷

关键词：

prediction on natural gas demand; ARIMA model; RBF neural network model; combined model;

D O I：

10.4028/www.scientific.net/AMR.869-870.533

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Based on the characteristics of natural gas demand trend, this paper proposed ARIMA model which can predict China's natural gas demand as an effective tool. Compared with the RBF neural network model and combined model, empirical results show that the accuracy and stability of the AMNIA model is best.

引用

页码：533 / 536

页数：4

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