Interpretable tourism volume forecasting with multivariate time series under the impact of COVID-19
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-07967-y.pdf
Reference54 articles.
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2. Karabulut G, Bilgin MH, Demir E, Doker AC (2020) How pandemics affect tourism: international evidence. Ann Touris Res 84:102991. https://doi.org/10.1016/j.annals.2020.102991
3. Hosseini SM, Paydar MM, Hajiaghaei-Keshteli M (2021) Recovery solutions for ecotourism centers during the Covid-19 pandemic: utilizing Fuzzy DEMATEL and Fuzzy VIKOR methods. Expert Syst Appl 185:115594. https://doi.org/10.1016/j.eswa.2021.115594
4. Kim YR, Liu A (2022) Social distancing, trust and post-COVID-19 recovery. Tour Manag 88:104416. https://doi.org/10.1016/j.tourman.2021.104416
5. Wickramasinghe K, Ratnasiri S (2021) The role of disaggregated search data in improving tourism forecasts: evidence from Sri Lanka. Curr Issues Tour 24:2740–2754. https://doi.org/10.1080/13683500.2020.1849049
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