@article{4373,
  author = {Gang Xu},
  title = {The Combination of Red Tourism Policy Tools Based on K-Means Clustering Algorithm},
  journal = {Journal of Intelligent Computing},
  year = {2025},
  volume = {16},
  number = {1},
  doi = {https://doi.org/10.6025/jic/2025/16/1/28-35},
  url = {https://www.dline.info/jic/fulltext/v16n1/jicv16n1_4.pdf},
  abstract = {Red tourism is a form of tourism with red tourist attractions and related historical culture as its theme. It is
significant for promoting historical and cultural preservation and economic development of tourism. The
configuration of the government’s red tourism policy tool combination is crucial for developing red tourism.
This study explores how to effectively configure the combination of red tourism policy tools to achieve
sustainable development of red tourism based on the K-means clustering algorithm. Firstly, red tourist
attractions are analyzed and clustered into different categories. Then, combining relevant historical and cultural
data and tourism economic data, the K-means clustering algorithm is applied to optimize the configuration of
red tourism policy tools. Through systematic research, we found that the configuration of red tourism policy
tools using the K-means clustering algorithm can effectively meet the needs of different categories of red tourist
attractions, thus promoting the sustainable development of red tourism. This research provides a valuable
reference for the government and relevant tourism agencies in configuring red tourism policy tools.},
}