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为解决新型城镇化与综合交通服务协同发展程度缺少定量描述的问题。以福建省为例,依据福建省9个地级市地区经济、城镇化率、综合交通服务水平建立起新型城镇化与综合交通服务协同分区指标体系,运用因子分析法对各指标提取出城市发展、运输水平、运输发展3个公因子,得出样本因子得分矩阵,在此基础上采用K-Means聚类法将福建省新型城镇化与综合交通服务协同发展分为3个类型区:优势发展区、潜在发展区、特色发展区,并得出3个类型区的公共因子得分矩阵。结果表明:因子分析法与K-Means聚类分析法相结合适用于新型城镇化与综合交通服务协同分区研究,所得聚类结果能有效聚合样本的同一性,并量化不同类型的差异性。
To solve the new urbanization and integrated transport services, the lack of quantitative description of the coordinated development of the problem. Taking Fujian Province for example, according to the economic, urbanization rate and comprehensive traffic service level of nine prefecture-level cities in Fujian Province, a new coordinated indexing system of urbanization and integrated transport services was established, and the indicators were extracted from urban development , Transportation level and transportation development, we get the sample factor score matrix. On this basis, the K-Means clustering method is used to divide the collaborative development of new urbanization and integrated transport services in Fujian Province into three types: Advantageous Development Area, potential development area and special development area, and get the public factor score matrix of 3 types of area. The results show that the combination of factor analysis and K-Means clustering analysis is suitable for the research of collaborative zoning of new urbanization and integrated transport services. The obtained clustering results can effectively aggregate the identities of samples and quantify the differences of different types.