<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>Exploring the strategy of integrating rural governance into tourism industry development is to provide industrial support to realize rural revitalization. This paper introduces recurrent neural networks and long and short-term memory neural networks under deep learning techniques, including their specific structures and basic principles, starting from artificial intelligence grading techniques. The basic principle of the attention mechanism is explained, and the components of the basic attention mechanism model structure and the steps of processing data are given. The ATT-LSTM analytical prediction model is jointly constructed using the attention mechanism and the long and short-term memory neural network, and the model’s prediction process and overall structure are given. The ATT-LSTM analysis model was used to analyze the data related to developing rural governance integrated tourism industry using county S as an example. From the satisfaction data, the percentages of very good, good, average, and poor ratings are 9.32%, 24.51%, 39.28%, and 26.89%, respectively. In terms of promotion and publicity, the percentage of visitors introduced by friends and family increased from 25.64% in 2017 to 33.58% in 2020, an increase of 30.97%. This shows that the use of artificial intelligence technology can effectively analyze the impact related to the integration and development of rural governance and the tourism industry and should be complemented by industrial advantages and natural resources to tap into local folk culture and thus promote the prosperous development of the tourism industry.</p>
</abstract>

Exploring the strategy of integrating rural governance into tourism industry development is to provide industrial support to realize rural revitalization. This paper introduces recurrent neural networks and long and short-term memory neural networks under deep learning techniques, including their specific structures and basic principles, starting from artificial intelligence grading techniques. The basic principle of the attention mechanism is explained, and the components of the basic attention mechanism model structure and the steps of processing data are given. The ATT-LSTM analytical prediction model is jointly constructed using the attention mechanism and the long and short-term memory neural network, and the model’s prediction process and overall structure are given. The ATT-LSTM analysis model was used to analyze the data related to developing rural governance integrated tourism industry using county S as an example. From the satisfaction data, the percentages of very good, good, average, and poor ratings are 9.32%, 24.51%, 39.28%, and 26.89%, respectively. In terms of promotion and publicity, the percentage of visitors introduced by friends and family increased from 25.64% in 2017 to 33.58% in 2020, an increase of 30.97%. This shows that the use of artificial intelligence technology can effectively analyze the impact related to the integration and development of rural governance and the tourism industry and should be complemented by industrial advantages and natural resources to tap into local folk culture and thus promote the prosperous development of the tourism industry.

A strategy study based on artificial intelligence data analysis of rural governance into tourism industry development research

Applied Mathematics and Nonlinear Sciences

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

Exploring the strategy of integrating rural governance into tourism industry development is to provide industrial support to realize rural revitalization. This...

A strategy study based on artificial intelligence data analysis of rural governance into tourism industry development research

Online veröffentlicht: 18. Aug. 2023

Seitenbereich: -

Eingereicht: 10. Okt. 2022

Akzeptiert: 27. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00212

Schlüsselwörter
Long and short-term memory neural network, Attention mechanism, ATT-LSTM analytical model, Deep learning, Tourism industry development.

© 2023 Hong Pan et al., published by Sciendo

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

A strategy study based on artificial intelligence data analysis of rural governance into tourism industry development research

Online veröffentlicht: 18. Aug. 2023

Seitenbereich: -

Eingereicht: 10. Okt. 2022

Akzeptiert: 27. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00212

SchlüsselwörterLong and short-term memory neural network, Attention mechanism, ATT-LSTM analytical model, Deep learning, Tourism industry development.

© 2023 Hong Pan et al., published by Sciendo

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

Schlüsselwörter
Long and short-term memory neural network, Attention mechanism, ATT-LSTM analytical model, Deep learning, Tourism industry development.