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<p>As an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development of local sports industry and economy. In this study, an integrated transfer learning model is constructed to assess the development level of rural revitalization by combining a constrained LightGBM-based learner, a Gaussian distribution and an optimized sampling function. Applying this model, this paper calculates the integrated development index of rural revitalization for 21 provinces, municipalities and autonomous regions in China between 2019 and 2023. Particularly for Tianjin, the study finds that its comprehensive development index for rural revitalization is relatively low, only 0.244 in 2023. Analyzing the cases of six typical villages in Tianjin, the study finds that sports tourism significantly impacts rural revitalization. During the five years, the average annual growth of tourist arrivals amounted to 125,400 visitors, and the average tourism revenue in 2023 reached 9.686 billion yuan. Meanwhile, these villages had an average of 3.79 points in the development level of living affluence, which is a high level. The study provides empirical support for sports tourism to help rural revitalization. It provides practical references for the future development direction and planning of rural sports tourism, emphasizing the critical role of sports tourism in promoting the comprehensive development of villages.</p>
</abstract>

As an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development of local sports industry and economy. In this study, an integrated transfer learning model is constructed to assess the development level of rural revitalization by combining a constrained LightGBM-based learner, a Gaussian distribution and an optimized sampling function. Applying this model, this paper calculates the integrated development index of rural revitalization for 21 provinces, municipalities and autonomous regions in China between 2019 and 2023. Particularly for Tianjin, the study finds that its comprehensive development index for rural revitalization is relatively low, only 0.244 in 2023. Analyzing the cases of six typical villages in Tianjin, the study finds that sports tourism significantly impacts rural revitalization. During the five years, the average annual growth of tourist arrivals amounted to 125,400 visitors, and the average tourism revenue in 2023 reached 9.686 billion yuan. Meanwhile, these villages had an average of 3.79 points in the development level of living affluence, which is a high level. The study provides empirical support for sports tourism to help rural revitalization. It provides practical references for the future development direction and planning of rural sports tourism, emphasizing the critical role of sports tourism in promoting the comprehensive development of villages.

A Logical Rationale for Sports Tourism to Help Rural Revitalization under Integrated Transfer Learning Strategy

Shan Dong Youth University of Political Science

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

As an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development...

A Logical Rationale for Sports Tourism to Help Rural Revitalization under Integrated Transfer Learning Strategy

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 10 ene 2024

Aceptado: 17 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0497

Palabras clave
Restricted LightGBM, Combined empowerment, Gaussian distribution, Sampling function, Rural revitalization

© 2024 Chen Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Logical Rationale for Sports Tourism to Help Rural Revitalization under Integrated Transfer Learning Strategy

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 10 ene 2024

Aceptado: 17 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0497

Palabras claveRestricted LightGBM, Combined empowerment, Gaussian distribution, Sampling function, Rural revitalization

© 2024 Chen Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Restricted LightGBM, Combined empowerment, Gaussian distribution, Sampling function, Rural revitalization