Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm
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 reg...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.01652 |
| _version_ | 1797340470733438976 |
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| author | Zheng Chengkang |
| author_facet | Zheng Chengkang |
| author_sort | Zheng Chengkang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T10:04:07Z |
| format | Article |
| id | doaj.art-3496af34ea944a42a6f2ac9ae4556f5a |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:04:07Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-3496af34ea944a42a6f2ac9ae4556f5a2024-01-29T08:52:45ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01652Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithmZheng Chengkang01Wuxi Vocational Institute of Arts & Technology, Yixing, Jiangsu, 214200, China.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.https://doi.org/10.2478/amns.2023.2.01652elastic network algorithmlinear regressionpenalty coefficientrural revitalization05c82 |
| spellingShingle | Zheng Chengkang Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm Applied Mathematics and Nonlinear Sciences elastic network algorithm linear regression penalty coefficient rural revitalization 05c82 |
| title | Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| title_full | Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| title_fullStr | Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| title_full_unstemmed | Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| title_short | Path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| title_sort | path analysis of tourism contributing to rural revitalization by combining elastic regression network algorithm |
| topic | elastic network algorithm linear regression penalty coefficient rural revitalization 05c82 |
| url | https://doi.org/10.2478/amns.2023.2.01652 |
| work_keys_str_mv | AT zhengchengkang pathanalysisoftourismcontributingtoruralrevitalizationbycombiningelasticregressionnetworkalgorithm |