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<p>Taking the Hani Terraces as an example, this study explores the classification and value evaluation of ecotourism resources in agricultural and cultural heritage sites, applying clustering algorithms with the aim of revealing their ecological, economic and social values and promoting the sustainable development of heritage sites. The study establishes an evaluation system including economic benefits, sightseeing resources, agricultural resources and ecological resources, and applies the gray system theory and cluster analysis method. Through the expert scoring of 27 evaluation indicators, combined with the gray clustering algorithm, the ecotourism resources of Hani Terraces were classified and valued. The results show that the vast majority of indicators (15/27) are rated as excellent, 11 indicators are good, and only 1 indicator is medium. In addition, the research on 80 households showed that the villagers’ perceived index of heritage protection averaged 4.44, the perceived index of ecological problems averaged 3.22, and the perceived index of tourism development averaged 3.84. In summary, the ecotourism resources of Hani Terraces have significant value and the local residents have a positive attitude towards their protection and development.</p>
</abstract>

Taking the Hani Terraces as an example, this study explores the classification and value evaluation of ecotourism resources in agricultural and cultural heritage sites, applying clustering algorithms with the aim of revealing their ecological, economic and social values and promoting the sustainable development of heritage sites. The study establishes an evaluation system including economic benefits, sightseeing resources, agricultural resources and ecological resources, and applies the gray system theory and cluster analysis method. Through the expert scoring of 27 evaluation indicators, combined with the gray clustering algorithm, the ecotourism resources of Hani Terraces were classified and valued. The results show that the vast majority of indicators (15/27) are rated as excellent, 11 indicators are good, and only 1 indicator is medium. In addition, the research on 80 households showed that the villagers’ perceived index of heritage protection averaged 4.44, the perceived index of ecological problems averaged 3.22, and the perceived index of tourism development averaged 3.84. In summary, the ecotourism resources of Hani Terraces have significant value and the local residents have a positive attitude towards their protection and development.

Classification and Value Evaluation of Ecotourism Resources in Agricultural and Cultural Heritage Sites Based on Clustering Algorithm--Taking Hani Terraces Globally Important Agricultural and Cultural Heritage Site as an Example

Applied Mathematics and Nonlinear Sciences

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

Taking the Hani Terraces as an example, this study explores the classification and value evaluation of ecotourism resources in agricultural and cultural...

Classification and Value Evaluation of Ecotourism Resources in Agricultural and Cultural Heritage Sites Based on Clustering Algorithm--Taking Hani Terraces Globally Important Agricultural and Cultural Heritage Site as an Example

Published Online: Feb 26, 2024

Page range: -

Received: Jan 17, 2024

Accepted: Jan 26, 2024

DOI: https://doi.org/10.2478/amns-2024-0660

Keywords
Evaluation system, Gray system theory, Cluster analysis, Gray clustering algorithm

© 2024 Tan Jiang et al., published by Sciendo

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

Classification and Value Evaluation of Ecotourism Resources in Agricultural and Cultural Heritage Sites Based on Clustering Algorithm--Taking Hani Terraces Globally Important Agricultural and Cultural Heritage Site as an Example

Published Online: Feb 26, 2024

Page range: -

Received: Jan 17, 2024

Accepted: Jan 26, 2024

DOI: https://doi.org/10.2478/amns-2024-0660

KeywordsEvaluation system, Gray system theory, Cluster analysis, Gray clustering algorithm

© 2024 Tan Jiang et al., published by Sciendo

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

Keywords
Evaluation system, Gray system theory, Cluster analysis, Gray clustering algorithm