The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology
Abstract With the rapid advancement of information and communication technologies, smart tourism has become a crucial means for improving the quality of tourism services and enhancing economic efficiency in the tourism sector. This work proposes an analysis method based on the artificial neural netw...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-94268-8 |
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| author | Yun Tian Xiaojie Tang |
| author_facet | Yun Tian Xiaojie Tang |
| author_sort | Yun Tian |
| collection | DOAJ |
| description | Abstract With the rapid advancement of information and communication technologies, smart tourism has become a crucial means for improving the quality of tourism services and enhancing economic efficiency in the tourism sector. This work proposes an analysis method based on the artificial neural network to predict tourist behavior patterns through big data analysis, thereby optimizing the allocation of tourism resources. The work begins by collecting various data types, including basic visitor information, consumption records, and satisfaction evaluations, from a well-known smart tourism destination as research samples. By carefully configuring and optimizing parameters such as learning rate, batch size, and optimizers, the work develops an efficient artificial neural network model. Experimental validation using real-world data demonstrates that the model excels across several performance metrics, including accuracy, recall, precision, and F1 score, and shows significant advantages over traditional statistical methods. In addition, the survey results show that users are highly satisfied with personalized service recommendations, resource optimization, and the overall user experience, with 75% of users expressing satisfaction. This work not only makes an academic contribution to the field of smart tourism but also demonstrates significant potential in improving tourism economic efficiency and enhancing the visitor experience. |
| format | Article |
| id | doaj-art-5f3ef7927f1b47c0b35a2a9634a0da6a |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5f3ef7927f1b47c0b35a2a9634a0da6a2025-08-20T03:01:23ZengNature PortfolioScientific Reports2045-23222025-03-0115111310.1038/s41598-025-94268-8The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technologyYun Tian0Xiaojie Tang1School of Business Administration, Jiangxi Vocational College of Industry and EngineeringSchool of Economics and Management, Jiangxi Vocational College of Industry and EngineeringAbstract With the rapid advancement of information and communication technologies, smart tourism has become a crucial means for improving the quality of tourism services and enhancing economic efficiency in the tourism sector. This work proposes an analysis method based on the artificial neural network to predict tourist behavior patterns through big data analysis, thereby optimizing the allocation of tourism resources. The work begins by collecting various data types, including basic visitor information, consumption records, and satisfaction evaluations, from a well-known smart tourism destination as research samples. By carefully configuring and optimizing parameters such as learning rate, batch size, and optimizers, the work develops an efficient artificial neural network model. Experimental validation using real-world data demonstrates that the model excels across several performance metrics, including accuracy, recall, precision, and F1 score, and shows significant advantages over traditional statistical methods. In addition, the survey results show that users are highly satisfied with personalized service recommendations, resource optimization, and the overall user experience, with 75% of users expressing satisfaction. This work not only makes an academic contribution to the field of smart tourism but also demonstrates significant potential in improving tourism economic efficiency and enhancing the visitor experience.https://doi.org/10.1038/s41598-025-94268-8Smart tourismInformation and communication technologyArtificial neural networksTourism economic efficiencyBig data analysis |
| spellingShingle | Yun Tian Xiaojie Tang The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology Scientific Reports Smart tourism Information and communication technology Artificial neural networks Tourism economic efficiency Big data analysis |
| title | The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| title_full | The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| title_fullStr | The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| title_full_unstemmed | The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| title_short | The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| title_sort | use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology |
| topic | Smart tourism Information and communication technology Artificial neural networks Tourism economic efficiency Big data analysis |
| url | https://doi.org/10.1038/s41598-025-94268-8 |
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