A study on the economic and sustainable development forecast of rural tourism industry based on ANN

Abstract

This study establishes a rural tourism industry economic sustainability prediction model based on the back propagation neural network (BP) in artificial neural network (ANN). It selects the indicators that have a large influence on the rural tourism industry economic sustainability prediction, and takes the four indicators with the highest weight percentage as the input of the prediction model, and verify the validity of the model. The result shows that the average relative prediction error of the univariate BP neural network was smaller than the grey model (GM). The average absolute value of relative prediction error for the multivariate BP neural network was smaller than the prediction error value of the univariate BP neural network model. The AUC value of the multivariate BP prediction model based on this study is 0.93. This research model improves the accuracy of predicting the sustainable economic development of the rural tourism industry.