Forecasting Oil Demand with the Development of Comprehensive Tourism

被引:7
|
作者
Huang, Yanrong [1 ]
Li, Shuaihao [2 ,3 ]
Wang, Rui [4 ,5 ]
Zhao, Zhijiang [1 ]
Huang, Bin [1 ]
Wei, Bo [6 ]
Zhu, Guangming [1 ]
机构
[1] Zhejiang Univ Water Resource & Electric Power, Coll Econ & Management, Hangzhou 310018, Peoples R China
[2] Sichuan Int Studies Univ, Sch Int Business & Management, Chongqing 400031, Peoples R China
[3] Sichuan Int Studies Univ, Res Ctr Int Business & Econ, Chongqing 400031, Peoples R China
[4] Jiangxi Univ Sci & Technol, Sch Econ & Management, Ganzhou 341000, Peoples R China
[5] Fujian Agr & Forestry Univ, Sch Econ, Fuzhou 350000, Peoples R China
[6] Zhejiang Sci Tech Univ, Sch Informat Sci & Technol, Hangzhou 310018, Peoples R China
关键词
oil demand; forecasting; comprehensive tourism; recurrent neutral network; ECONOMIC-GROWTH; CONSUMPTION;
D O I
10.1007/s10553-021-01250-x
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
The prediction of oil demand is an important issue related to national energy security and economic development. With the COVID-19 outbreak, the international oil price fluctuates sharply, and oil consumption growth slows down. Therefore, accurate prediction of oil demand plays an important practical and theoretical role. In this paper, in accordance with the Chinese state policy stimulation of domestic demand for energy resources, we have selected 15 major factors and analyzed their influence on the domestic oil demand from the perspective of comprehensive tourism analysis. Based on the data analysis of oil consumption from 2000 to 2018, four neutral network methods are used to predict the influence of selected factors on oil consumption demand of China. The experimental results show that the best correlation is obtained between domestic tourism revenue and total tourism expenditure factors and oil demand, and the Layer Recurrent Neutral Network method has high prediction accuracy, stronger stability, and the best performance.
引用
收藏
页码:299 / 310
页数:12
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