Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm
作者：
Highlights：
• Multi-step ahead demand forecasting is an important and cutting-edge research topic.
• An effective forecasting approach incorporating privileged information is proposed.
• The new paradigm (termed learning using privileged information (LUPI)) is imployed.
• LUPI can efficiently grasp and model nonlinear characteristics of tourism data.
• The empirical results verify its superiority and robustness with different samples.
摘要
•Multi-step ahead demand forecasting is an important and cutting-edge research topic.•An effective forecasting approach incorporating privileged information is proposed.•The new paradigm (termed learning using privileged information (LUPI)) is imployed.•LUPI can efficiently grasp and model nonlinear characteristics of tourism data.•The empirical results verify its superiority and robustness with different samples.
论文关键词：Tourism demand,Multi-step ahead forecasting,Privileged information,Machine learning,Kernel random vector functional link network
论文评审过程：Received 2 March 2022, Revised 31 July 2022, Accepted 8 August 2022, Available online 12 August 2022, Version of Record 21 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118502
