Research on cluster system distribution of traditional fort-type settlements in Shaanxi based on K-means clustering algorithm

Taking the traditional fort-type settlements in Shaanxi as the research object, quantitative research methods such as K-means clustering algorithm, correlation analysis, density analysis, and nearest neighbor index are used to study their spatial distribution, formation causes, and cluster characteristics. The objective of the study is to break through the geographical limitations of fort-type settlements research and to explore the scientific methods of classifying and analyzing traditional fort-type settlements. The conclusions are: (1) The results of cluster analysis show that the fort-type settlements in Shaanxi can be divided into three categories; (2) The overall distribution of fort-type settlements in Shaanxi shows multi-point aggregation, and contains both point and linear aggregation distribution; (3) There are four typical cluster systems among the traditional fort-type settlements in Shaanxi; (4) The factors that have the greatest influence on the distribution of settlements are construction force, wall masonry, age, fortification purpose, and topographic environment. The article innovatively proposes the cluster system perspective and introduces mathematical algorithms and quantitative research methods to study the cluster system of the fort-type Settlements. This approach is feasible and can be applied to other settlement-related studies. At the same time, the perspective of cluster system could be used in heritage conservation, which can contribute to the restoration of architectural relics and systemic conservation on a larger scale.

Automated summary

This study focuses on the traditional fort-type settlements in Shaanxi, using quantitative research methods such as K-means clustering algorithm and correlation analysis to study their spatial distribution and cluster characteristics. The results show that these settlements can be divided into three categories, and their overall distribution exhibits multi-point aggregation. The innovative research approach can be applied to other settlement-related studies and also has implications for heritage conservation.