Tourism demand forecasting: An ensemble deep learning approach

doi:10.1177/13548166211025160

CSpace

	Tourism demand forecasting: An ensemble deep learning approach
	Sun, Shaolong 1; Li, Yanzhao 1; Guo, Ju-e 1; Wang, Shouyang 2,3,4
	2021-07-01
发表期刊	TOURISM ECONOMICS
ISSN	1354-8166
页码	29
摘要	The availability of tourism-related big data increases the potential to improve the accuracy of tourism demand forecasting but presents significant challenges for forecasting, including curse of dimensionality and high model complexity. A novel bagging-based multivariate ensemble deep learning approach integrating stacked autoencoder and kernel-based extreme learning machine (B-SAKE) is proposed to address these challenges in this study. By using historical tourist arrival data, economic variable data, and search intensity index (SII) data, we forecast tourist arrivals in Beijing from four countries. The consistent results of multiple schemes suggest that our proposed B-SAKE approach outperforms the benchmark models in terms of level accuracy, directional accuracy, and even statistical significance. Both bagging and stacked autoencoder can effectively alleviate the challenges brought by tourism big data and improve the forecasting performance of the models. The ensemble deep learning model we propose contributes to tourism demand forecasting literature and benefits relevant government officials and tourism practitioners.
关键词	bagging economic variables ensemble deep learning search intensity index stacked autoencoder tourism demand forecasting
DOI	10.1177/13548166211025160
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[71988101] ; National Natural Science Foundation of China[71642006] ; Fundamental Research Funds for the Central Universities[SK2021007]
WOS研究方向	Business & Economics ; Social Sciences - Other Topics
WOS类目	Economics ; Hospitality, Leisure, Sport & Tourism
WOS记录号	WOS:000671417000001
出版者	SAGE PUBLICATIONS LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/58882
专题	中国科学院数学与系统科学研究院
通讯作者	Sun, Shaolong
作者单位	1.Xi An Jiao Tong Univ, Sch Management, 28 Xianning West Rd, Xian 710049, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Management Sci, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Management Sci & Engn, Beijing, Peoples R China 4.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Sun, Shaolong,Li, Yanzhao,Guo, Ju-e,et al. Tourism demand forecasting: An ensemble deep learning approach[J]. TOURISM ECONOMICS,2021:29.
APA	Sun, Shaolong,Li, Yanzhao,Guo, Ju-e,&Wang, Shouyang.(2021).Tourism demand forecasting: An ensemble deep learning approach.TOURISM ECONOMICS,29.
MLA	Sun, Shaolong,et al."Tourism demand forecasting: An ensemble deep learning approach".TOURISM ECONOMICS (2021):29.