<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the process of modernization and development, intelligent technology empowers rural tourism, which in turn enables the effective implementation of the rural revitalization strategy. In this paper, a rural tourism recommendation model combined with artificial intelligence technology is constructed, which effectively improves the accuracy and personalization level of tourist attraction recommendation by mining and analyzing tourism data and extracting tourism characteristic factors. Secondly, the random forest classification algorithm is used to establish a random forest preference attraction prediction model, and several recommendation algorithms are combined to design a personalized rural tourism recommendation model to improve the accuracy of tourists’ tourism recommendations. Finally, the countryside around a city is being investigated to explore the modern development of rural tourism and help revitalize rural areas. The results show that the number of people received by rural tourism in City A and the number of tourists received by the province in 2022 is 972 million and 1,424 million more than that of 2014, and the total income from rural tourism in City A and the total income from tourism in the province in 2022 is 724.8 billion and 1,202.02 billion yuan more than that of 2014, and it can be seen that the high level of tourism income maintains a positive correlation with the number of tourists received. It shows that rural tourism improves the overall economic level of the countryside, accelerates the process of social progress in rural areas, and strongly contributes to the modernization and development of rural revitalization.</p>
</abstract>

In the process of modernization and development, intelligent technology empowers rural tourism, which in turn enables the effective implementation of the rural revitalization strategy. In this paper, a rural tourism recommendation model combined with artificial intelligence technology is constructed, which effectively improves the accuracy and personalization level of tourist attraction recommendation by mining and analyzing tourism data and extracting tourism characteristic factors. Secondly, the random forest classification algorithm is used to establish a random forest preference attraction prediction model, and several recommendation algorithms are combined to design a personalized rural tourism recommendation model to improve the accuracy of tourists’ tourism recommendations. Finally, the countryside around a city is being investigated to explore the modern development of rural tourism and help revitalize rural areas. The results show that the number of people received by rural tourism in City A and the number of tourists received by the province in 2022 is 972 million and 1,424 million more than that of 2014, and the total income from rural tourism in City A and the total income from tourism in the province in 2022 is 724.8 billion and 1,202.02 billion yuan more than that of 2014, and it can be seen that the high level of tourism income maintains a positive correlation with the number of tourists received. It shows that rural tourism improves the overall economic level of the countryside, accelerates the process of social progress in rural areas, and strongly contributes to the modernization and development of rural revitalization.

Rural tourism incorporating artificial intelligence technology to help modernize rural revitalization

Applied Mathematics and Nonlinear Sciences

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

In the process of modernization and development, intelligent technology empowers rural tourism, which in turn enables the effective implementation of the rural...

Rural tourism incorporating artificial intelligence technology to help modernize rural revitalization

Publié en ligne: 06 déc. 2023

Pages: -

Reçu: 14 mars 2023

Accepté: 16 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01379

Mots clés
Artificial intelligence technology, Mining analysis, Random forest classification, Recommendation algorithm, Rural revitalization

© 2023 Lu Gan, published by Sciendo

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

Rural tourism incorporating artificial intelligence technology to help modernize rural revitalization

Publié en ligne: 06 déc. 2023

Pages: -

Reçu: 14 mars 2023

Accepté: 16 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01379

Mots clésArtificial intelligence technology, Mining analysis, Random forest classification, Recommendation algorithm, Rural revitalization

© 2023 Lu Gan, published by Sciendo

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

Mots clés
Artificial intelligence technology, Mining analysis, Random forest classification, Recommendation algorithm, Rural revitalization