Research on Spatial Differences and Evolution of Agricultural Parks Based on Topological Segmentation and Cluster Analysis

Abstract

When analyzing the evolution of spatial differences in agricultural parks, the boundaries of spatial data of common evolution models are not obvious, which leads to the lack of generalization ability of the models. Faced with this problem, this paper puts forward a modeling analysis of spatial differences and evolution of agricultural parks based on topological segmentation and cluster analysis. Cluster analysis technology is used to process the spatial data of agricultural parks. To facilitate the subsequent segmentation, the cluster data is converted into graph data, and then the low-dimensional data space is constructed by mapping. Topological segmentation technology is used to divide the data space into multiple unit spaces according to the spatial differences and cluster analysis results. The efficiency value of each unit space is calculated, and the cross-efficiency evaluation model is established. Combined with the comprehensive relative efficiency of unit spaces, the evolution model is constructed. The test results show that: the spatial data clustering boundary of the designed evolutionary model based on topological segmentation and clustering analysis is obvious. The model has good synergy with internal factors and short evolutionary running time. Its overall generalization ability is enhanced. The study provides certain reference for studying the spatial characteristics of agricultural parks under the influence of different regional environments.