Forecast daily tourist volumes during the epidemic period using COVID-19 data, search engine data and weather data
作者：
Highlights：
• A novel framework is proposed for daily tourist volume forecasting.
• The method uses variational mode decomposition and gated recurrent unit networks.
• Distance correlation coefficient is adopted to select search traffic data.
• COVID-19 data is of greatest significance for forecasting.
• The proposed approach is excellent in forecasting non-stationary tourist volume.
摘要
•A novel framework is proposed for daily tourist volume forecasting.•The method uses variational mode decomposition and gated recurrent unit networks.•Distance correlation coefficient is adopted to select search traffic data.•COVID-19 data is of greatest significance for forecasting.•The proposed approach is excellent in forecasting non-stationary tourist volume.
论文关键词：Tourist volume forecasting,COVID-19 data,Search traffic data,Variational mode decomposition,Gated recurrent unit network
论文评审过程：Received 27 April 2022, Revised 5 August 2022, Accepted 8 August 2022, Available online 12 August 2022, Version of Record 17 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118505
