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<p>This article discusses the high-level guidance strategy and deep-level value embodiment of tourism informatization construction for smart city tourism. Based on the existing evaluation system of intelligent city tourism development, the article utilizes BP neural network for data screening. It combines the entropy weight method to complete the index assignment, and evaluates and analyzes the development of innovative tourism services in six intelligent cities. In the area of brilliant tourism information service, Beijing scored 94%. In clever catering and accommodation services, Beijing leads with a score of 90%, while Nanjing and Chengdu rank second and third with scores of 81% and 80% respectively. Regarding overall innovative tourism development, Beijing scored 0.4731, 0.1762, and 0.1168 in terms of scientific and technological innovation, economic development, and general development security, respectively. In addition, the intelligent tourism development trend from 2018 to 2022 shows that Beijing’s tourism revenue will reach 622.46 billion yuan in 2022, which is 30.36 billion yuan more than the previous year. By evaluating the development of intelligent city tourism services through BP neural network, this paper effectively identifies the critical factors for developing clever tourism construction. It puts forward effective strategies to improve the level of intelligent services. These findings have important theoretical and practical significance for the development of intellectual city tourism field, and provide an essential reference for the further optimization of smart city tourism services.</p>
</abstract>

This article discusses the high-level guidance strategy and deep-level value embodiment of tourism informatization construction for smart city tourism. Based on the existing evaluation system of intelligent city tourism development, the article utilizes BP neural network for data screening. It combines the entropy weight method to complete the index assignment, and evaluates and analyzes the development of innovative tourism services in six intelligent cities. In the area of brilliant tourism information service, Beijing scored 94%. In clever catering and accommodation services, Beijing leads with a score of 90%, while Nanjing and Chengdu rank second and third with scores of 81% and 80% respectively. Regarding overall innovative tourism development, Beijing scored 0.4731, 0.1762, and 0.1168 in terms of scientific and technological innovation, economic development, and general development security, respectively. In addition, the intelligent tourism development trend from 2018 to 2022 shows that Beijing’s tourism revenue will reach 622.46 billion yuan in 2022, which is 30.36 billion yuan more than the previous year. By evaluating the development of intelligent city tourism services through BP neural network, this paper effectively identifies the critical factors for developing clever tourism construction. It puts forward effective strategies to improve the level of intelligent services. These findings have important theoretical and practical significance for the development of intellectual city tourism field, and provide an essential reference for the further optimization of smart city tourism services.

Exploring the High-Quality Development of Smart City Tourism in the Information Age

Applied Mathematics and Nonlinear Sciences

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

This article discusses the high-level guidance strategy and deep-level value embodiment of tourism informatization construction for smart city tourism. Based...

Exploring the High-Quality Development of Smart City Tourism in the Information Age

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 10 ene 2024

Aceptado: 15 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0457

Palabras clave
BP neural network, Entropy weight method, Smart city tourism, Informatization

© 2024 Manman Liu, published by Sciendo

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

Exploring the High-Quality Development of Smart City Tourism in the Information Age

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 10 ene 2024

Aceptado: 15 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0457

Palabras claveBP neural network, Entropy weight method, Smart city tourism, Informatization

© 2024 Manman Liu, published by Sciendo

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

Palabras clave
BP neural network, Entropy weight method, Smart city tourism, Informatization