Tourism Demand Interval Forecasting Amid COVID-19: A Hybrid Model With a Modified Multi-Objective Optimization Algorithm

A hybrid tourism demand interval forecasting system is proposed consisting of two parts: the construction of forecasting interval based on lower and upper bound estimates, and the forecasting interval adjustment based on an optimized reduction coefficient. Coronavirus factors are added as input variables to improve forecasting performance. A new multi-objective optimization algorithm is proposed to construct a feature selection method, optimize the forecasting model, and estimate the optimal reduction coefficient. The results of the experiments show that the proposed system has a powerful interval forecasting ability, which provides crucial guidance for balancing the recovery of the tourism industry and the control of the epidemic spread during the COVID-19 pandemic, and contributes to contingency planning for tourism practitioners and managers.

Automated summary

A hybrid tourism demand interval forecasting system is proposed, which includes the construction of forecasting interval based on lower and upper bound estimates, and the adjustment of forecasting interval based on an optimized reduction coefficient. Coronavirus factors are included as input variables to enhance forecasting performance. A new multi-objective optimization algorithm is developed for feature selection, model optimization, and estimating the optimal reduction coefficient. Experimental results demonstrate that the proposed system has a strong ability in interval forecasting, providing crucial guidance for balancing tourism industry recovery and COVID-19 epidemic control, as well as contributing to contingency planning for tourism practitioners and managers.