中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 数学与系统科学研究院
  3. 中国科学院数学与系统科学研究院
Tourism demand forecasting: An ensemble deep learning approach

文献类型：期刊论文

作者Sun, Shaolong4; Li, Yanzhao4; Guo, Ju-e4; Wang, Shouyang1,2,3
刊名TOURISM ECONOMICS
出版日期2021-07-01
页码29
关键词bagging economic variables ensemble deep learning search intensity index stacked autoencoder tourism demand forecasting
ISSN号1354-8166
DOI10.1177/13548166211025160
英文摘要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.
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
语种英语
WOS记录号WOS:000671417000001
出版者SAGE PUBLICATIONS LTD
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/58881]  
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.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Management Sci & Engn, Beijing, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Management Sci, Beijing, Peoples R China
4.Xi An Jiao Tong Univ, Sch Management, 28 Xianning West Rd, Xian 710049, 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.

入库方式： OAI收割

来源：数学与系统科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。