企业分布数据的多级网格划分方法

Zhang Zhang, Yangyang Zhao, Lina Duan, A. Qiu, Fuhao Zhang, Kunwang Tao
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摘要

为了有效利用企业分布数据,实现企业分布数据的社会经济价值最大化,提出了一种企业分布数据多层次网格划分方法,将海量数据划分为合理的大小。该方法以全国各省(市)为最粗划分,根据企业所在位置构造四叉树对企业点进行划分。四叉树中的每个节点都有一个点的极限,当一个节点的点的数量超过这个极限时,该节点被分成四个节点,每个象限的点的数量大致相同。这个过程递归地进行,直到没有节点包含超过限制的点。利用哈尔滨市企业分布数据进行实验,验证了该方法的可行性和有效性,实验结果表明,将企业分布数据快速准确地划分到网格中,提高了数据的适用性和数据集成的便利性。
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A Multi-level Grid Partition Method for Enterprises Distribution Data
In order to use enterprises' distribution data effectively and maximize their social and economic values, a multi-level grid partition method for enterprise distribution data is proposed which divides the voluminous data into reasonable size. This method uses the provinces or municipalities of nationwide as the coarsest division, then a quad-tree is constructed to partition the points of enterprises according to their locations. Each node in the quad-tree has a limit of points, when the number of points in a node beyond the limit, the node is divided into four nodes with roughly the same number of points in each quadrant. This process proceeds recursively until no node contains points more than the limit. Enterprise distribution data of Harbin is used in experiments to test the feasibility and effectiveness of this method, the results of the experiments show that the enterprises distribution data are divided rapidly and accurately to the grid, which improve the applicability of the data and the convenience of data integration.
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