Journal of Engineering, Project, and Production Management, 2026, 16(5), 2026-4
Using SOM Fusion Algorithms and Development Planning Strategies for Traditional Village Classification
1 Lecturer,
Architecture Engineering College, Huanghuai University, Zhumadian,
463000, China
2 Lecturer, College of Animal
Husbandry Engineering, Zhumadian Agricultural Engineering Vocational
College, Zhumadian, 463000, China
3 Lecturer, Architecture and
Engineering College of Huanghuai University, Zhumadian, 463000, China,
E-mail: wanngqiann@outlook.com (corresponding author).
Project Management
Received January 4, 2026; revised March 4, 2026; accepted July 13, 2026
Available online July 25, 2026
Abstract: In response to the problems of inaccurate classification and homogeneous strategies in the protection and development of traditional villages, this study aims to construct a data-driven village classification and differentiated development planning strategy system. By introducing a clustering method that combines self-organizing mapping and the K-means algorithm, automated, high-precision classification of villages' multi-dimensional features can be achieved. By combining the analytic hierarchy process and the entropy weight method for weighting, a village development evaluation index system is constructed to accurately identify development shortcomings. The experimental findings demonstrate that, when testing the classification accuracy of the research method, accuracy gradually increases to 92.5% as the data volume increases to 250. When the number of clusters is 5, the central processing unit takes only 3.4 seconds. In practical application, the highest employment rate for the research method is 58.2%, from the implementation year through the 5th year of the strategy. When the neighborhood radius is 6, the highest contour coefficient is 0.72. When the data missing rate is 0%, the highest adjusted Rand index of the research method reaches 0.91. The outcomes indicate that the research method has higher classification accuracy, computational efficiency, and better robustness, providing scientific methods for precise classification and development of traditional villages, as well as a quantitative decision-making basis for differentiated management of rural revitalization.
Keywords: Village classification; SOM fusion algorithm; development planning strategy; combination weighting; development indicator system.
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Citation: Qin, K., Li, C., and Wang, Q. (2026). Using SOM Fusion Algorithms and Development Planning Strategies for Traditional Village Classification. Journal of Engineering, Project, and Production Management, 16(5), 2026-4.
