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<p>This paper constructs the basic framework of the spatial pattern analysis method of historical, cultural heritage with the relevant technology of artificial intelligence and analyzes the spatial pattern of historical cultural heritage through spatial correlation analysis. ArcGIS and FineBI software are used to carry out correlation analysis on the degree of spatial aggregation, spatial distribution density, and related point and line distribution of cultural heritage tourism resources so as to derive the spatial distribution characteristics of cultural heritage tourism resources. Shanzhou Region, Sanmenxia City, Henan Province, is taken as the research object to empirically analyze the development and protection of its cultural heritage tourism resources. The results show that the values of global autocorrelation Moran’s I of spatial mismatch of cultural heritage tourism resources are all positive, and the mean value of Z(I) is 6.07956, P(I)&lt;0.05, indicating that the spatial mismatch index of cultural heritage tourism resources at the city level has a significant spatial clustering tendency and an obvious clustering tendency. This study offers scientific suggestions for the development of cultural heritage resources in tourism, and it is also crucial for the development of Chinese cultural heritage sites.</p>
</abstract>

This paper constructs the basic framework of the spatial pattern analysis method of historical, cultural heritage with the relevant technology of artificial intelligence and analyzes the spatial pattern of historical cultural heritage through spatial correlation analysis. ArcGIS and FineBI software are used to carry out correlation analysis on the degree of spatial aggregation, spatial distribution density, and related point and line distribution of cultural heritage tourism resources so as to derive the spatial distribution characteristics of cultural heritage tourism resources. Shanzhou Region, Sanmenxia City, Henan Province, is taken as the research object to empirically analyze the development and protection of its cultural heritage tourism resources. The results show that the values of global autocorrelation Moran’s I of spatial mismatch of cultural heritage tourism resources are all positive, and the mean value of Z(I) is 6.07956, P(I)<0.05, indicating that the spatial mismatch index of cultural heritage tourism resources at the city level has a significant spatial clustering tendency and an obvious clustering tendency. This study offers scientific suggestions for the development of cultural heritage resources in tourism, and it is also crucial for the development of Chinese cultural heritage sites.

Research on Development and Protection of Cultural Heritage Tourism Resources in the Age of Artificial Intelligence

Applied Mathematics and Nonlinear Sciences

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

This paper constructs the basic framework of the spatial pattern analysis method of historical, cultural heritage with the relevant technology of artificial...

Research on Development and Protection of Cultural Heritage Tourism Resources in the Age of Artificial Intelligence

Publicado en línea: 20 dic 2023

Páginas: -

Recibido: 29 ene 2023

Aceptado: 30 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01554

Palabras clave
Artificial intelligence, Spatial pattern, Distribution density, Moran’s I, Tourism resources development

© 2023 Li Cheng, published by Sciendo

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

Research on Development and Protection of Cultural Heritage Tourism Resources in the Age of Artificial Intelligence

Publicado en línea: 20 dic 2023

Páginas: -

Recibido: 29 ene 2023

Aceptado: 30 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01554

Palabras claveArtificial intelligence, Spatial pattern, Distribution density, Moran’s I, Tourism resources development

© 2023 Li Cheng, published by Sciendo

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

Palabras clave
Artificial intelligence, Spatial pattern, Distribution density, Moran’s I, Tourism resources development