International Tourism Revenue Projections for Guilin in the Context of COVID-19

Abstract

This paper collects relevant international tourism revenue data for Guilin from 2004 to 2020 for analysis and modelling using three algorithms, namely multiple linear regression model, support vector machine and random forest, to explore the variables affecting international tourism revenue in Guilin and to make model predictions for international tourism revenue from 2019 to 2020. The empirical evidence shows that the multiple linear regression model predicts the best results, especially the accurate prediction of the sharp decline in international tourism revenue when the new crown pneumonia epidemic spreads in 2020 , which can provide some scientific basis tourism development planning of Guilin city in the future.