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An analysis of regional product by Three Strata of Industry based on K-means method

机译：基于K-MERIC法的三层地层区域产物分析

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This study applies cluster analysis K-means method to analyze the data of regional product by Three Strata of Industry in China. Firstly, we give a review of K-means method, according to self-organizing feature maps we determine the number of clusters, and then employ the K-means method to find the clusters. From the cluster analysis we get four clusters and conclude that the membership in Cluster 1 are all municipalities with the highest value of Per Capita GRP and the highest percentage composition of Tertiary Industry. It shows that the economy of this cluster is developed. Cluster 2 with the lowest composition of Tertiary Industry should enhance the development of Tertiary Industry. The Secondary Industry of Cluster 3 is the most developed. The most provinces in China concentrate in Cluster 4 with the lowest Per Capita GRP need to enhance both Secondary Industry and Tertiary Industry.
机译：本研究适用于集群分析K-Means方法，以分析中国工业的三层地区的区域产品数据。 首先，我们对K-means方法进行了审查，根据自组织特征映射我们确定群集的数量，然后采用K-Means方法来找到群集。 从集群分析中，我们得到了四个集群并得出结论，集群1的成员资格是具有人均最高价值的城市，以及第三产业的最高百分比组成。 它表明，开发了该集群的经济。 第2群，第三产业最低的组成应增强第三产业的发展。 集群3的二级行业是最发达的。 中国最多的省份集中于集群4，人均最低的GRP需要加强二级行业和第三产业。

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