Design of a Cultural Tourism Passenger Flow Prediction Model in the Yangtze River Delta Based on Regression Analysis

Abstract

Cultural tourism has gained much attention in the last decade and has promoted the preservation of a variety of tangible and intangible assets of culture. In order to accurately predict the cultural tourism passenger flow in the Yangtze River Delta and improve its economic benefits, this paper designs the prediction model of cultural tourism passenger flow in the Yangtze River Delta based on regression analysis. Taking the competitiveness of passenger flow as the core, this paper selects 28 indexes from four aspects of cultural tourism brand resources, cultural tourism support and protection, and urban tourism market income to build the evaluation index system of influencing factors of passenger flow. The principal component analysis method is used to simplify many related factors into a few uncorrelated factors to eliminate the multicollinearity caused by too many dependent variables; on this basis, the principal component regression model is constructed, and the determination coefficient is used to test the model fitting. Taking 15 cultural tourism cities in the Yangtze River Delta as the research object, the results show that the designed model has a good fitting degree, and the average error is only 0.41%, which can meet the needs of the prediction of cultural tourism passenger flow in the Yangtze River Delta. After the application of the prediction model, the foreign exchange earning amount of each cultural tourism city can be increased by more than 12%. The study has revealed good results.