Application of COEMD-S-SVR model in tourism demand forecasting and economic behavior analysis: The case of Sanya City

被引:6
作者
Fan, Guo-Feng [1 ]
Jin, Xiang-Ru [1 ]
Hong, Wei-Chiang [2 ]
机构
[1] Pingdingshan Univ, Pingdingshan, Peoples R China
[2] Jiangsu Normal Univ, Xuzhou, Peoples R China
关键词
Tourism demand forecasting; economic behavior analysis; empirical mode decomposition (EMD); support vector regression (SVR); error factor adjustment; rectangular-ambulatory matrix; BP NEURAL-NETWORK; TIME-SERIES; DECOMPOSITION; EMD; ACCURACY;
D O I
10.1080/01605682.2021.1915192
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Tourism industry played an increasingly prominent role in the socio-economic development in China. Therefore, it is of great significance to forecast the tourism demand, to analyze the development tendency of tourism, to explore the mode of economic linkage, and eventually to reveal the development regulation of tourism industry. In this paper, the empirical mode decomposition, the support vector regression, and the error factor adjustment were combined to forecast the tourism demand of Sanya City. The results demonstrate that the proposed model is more accurate than other models. Meanwhile, this paper also provides the insight analyses of the economic behavior through the tourism demand's rectangular-ambulatory matrix. The analyses reveal the regulation of tourism industry and the future benefits of Sanya's tourism.
引用
收藏
页码:1474 / 1486
页数:13
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