Enhancing tourism demand forecasting with two-stage feature selection and attention-augmented deep learning models
文献类型：期刊论文
| 作者 | Wei, Jinghui4,5; Wu, Sheng1,5; Cheng, Shifen2,3 |
| 刊名 | CURRENT ISSUES IN TOURISM
 |
| 出版日期 | 2026-01-22 |
| 卷号 | N/A |
| 关键词 | Tourism demand forecasting Time2Vec two-stage feature selection attention-augmented |
| ISSN号 | 1368-3500 |
| DOI | 10.1080/13683500.2026.2616316 |
| 产权排序 | 4 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Accurate tourism demand forecasting is essential for regional planning and industry development. However, existing models often struggle with the complexity of external variables and fail to capture multi-level temporal correlations, limiting their accuracy and robustness. This study introduces the Tourism Demand Predictor with Two-Stage Feature Selection and Attention-Augmented Mechanisms (TFS-AAM). The model employs a two-stage feature selection strategy to refine predictive variables and integrates a Time2Vec-enhanced multi-scale attention mechanism to effectively capture short-term fluctuations and long-term trends. Extensive experiments on three tourism datasets demonstrate TFS-AAM's superior performance compared to eight baseline methods. Notably, TFS-AAM exhibits strong robustness during periods of high tourist demand and sudden fluctuations, underscoring its practical value for data-driven decision-making and strategic planning in the tourism industry. |
| URL标识 | 查看原文 |
| WOS研究方向 | Social Sciences - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001666492000001 |
| 出版者 | ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219621]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Wu, Sheng |
| 作者单位 | 1.Minist Educ, Key Lab Spatial Data Min & Informat Sharing, Fuzhou, Peoples R China; 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China; 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Fuzhou Univ, Coll Comp & Data Sci, Fuzhou, Peoples R China; 5.Fuzhou Univ, Acad Digital China Fujian, Fuzhou, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wei, Jinghui,Wu, Sheng,Cheng, Shifen. Enhancing tourism demand forecasting with two-stage feature selection and attention-augmented deep learning models[J]. CURRENT ISSUES IN TOURISM,2026,N/A. |
| APA | Wei, Jinghui,Wu, Sheng,&Cheng, Shifen.(2026).Enhancing tourism demand forecasting with two-stage feature selection and attention-augmented deep learning models.CURRENT ISSUES IN TOURISM,N/A. |
| MLA | Wei, Jinghui,et al."Enhancing tourism demand forecasting with two-stage feature selection and attention-augmented deep learning models".CURRENT ISSUES IN TOURISM N/A(2026). |
入库方式： OAI收割
来源：地理科学与资源研究所
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