Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm

Abstract

The development of suitable tourism according to the countryside’s local conditions can greatly help to improve the overall economic level of rural areas. This paper uses the elastic network method to optimize the penalty coefficient of the regression model so as to construct the elastic network regression model. In order to explore the effective path of tourism to help rural revitalization, this paper, through the selection of research variables, takes rural revitalization farmers’ income as an explanatory variable and tourism income as a core explanatory variable. The impact of tourism on rural revitalization was analyzed in several ways, including descriptive statistics of variables, coupling relationship tests, and benchmark regression. The results show that the mean value of farmers’ income in rural revitalization has increased by 5.045 compared with the minimum value, and the tourism industry has helped the local farmers achieve income generation to a certain extent. The disposable income of farmers is in the interval of [-1.8,-1.2], the level of agro-tourism integration is in the interval of [9,10], and the level of agro-tourism integration is positively correlated with the disposable income of farmers. The regression coefficient of industrial affairs expenditure is 0.503, which has a positive effect on tourism income at a 1% significance level. Tourism enhances the implementation effect of rural revitalization in the form of increasing farmers’ disposable income, and provides new help to optimize the rural industrial structure and enhance the ecological development level of tourism products.

Keywords

• elastic network algorithm
• linear regression
• penalty coefficient
• rural revitalization
• 05c82