基于Kruskal算法和主成分分析的农业经济信息评价  

Comprehensive Evaluation of Agricultural Economic Information Based on Kruskal Algorithm Combined with Principal Component Analysis

作　　者：杨玉建[1] 朱建华[1] 

机构地区：[1]山东省农业科学院科技信息工程技术研究中心,山东济南250100

出　　处：《山东农业科学》2010年第2期24-26,共3页Shandong Agricultural Sciences

摘　　要：为了解县域单元内部乡镇之间农业经济信息的空间格局及结构,以山东省禹城市11个乡镇为研究对象,重点选取了反映农业经济信息的农业机械总动力等9项指标,运用主成分分析的统计方法,建立了农业经济信息的主成分载荷矩阵,计算了农业经济信息主成分综合得分,从计算机学科图论的角度入手,结合Kruskal求解最小生成树算法从定量的角度分析了禹城市11个乡镇农业经济信息的综合潜力状况,利用Kruskal算法和主成分结合的方法对乡镇单元尺度进行农业经济信息分析,确定最佳的区位优势、分类和组合,以便于农业的集约化和耕作的合理化,较好地配置农业的产业结构,为农业可持续发展和实现合理的农业地域分工提供科学依据。The paper aimed to understand the spatial pattern and structure of agricultural economic information of villages and towns on the county scale by using the two dimensional graph theory - clustering method with spatial analysis technique. With 11 towns of Yucheng City in Shandong Province as the cases, 9 indicators such as the total power of agricultural machinery were analyzed by the principal component analysis. Then the principal component matrix was established about the agricultural economy information, and the score sequence of the principal component of the agricultural economy information was computerized. The Kruskal algorithm of Graph - Theory in Computer Science was used to analyze the potential status of agricultural economic information of 11 towns of Yucheng City. The optimal location superiority, the classification and the combination were determined in order to make the agricultural intensification and cultivation rationalization and well dispose the industrial structure, which would provide scientific basis for agricultural sustainable development and realize the reasonable territorial division of labor in agriculture.

关 键 词：KRUSKAL算法 主成分分析 农业经济信息 尺度 

分 类 号：F302.4[经济管理—产业经济]