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为提高海量空间数据访问形成的空间统计数据传输服务质量,提出一种云计算环境下空间统计数据的点云聚类压缩算法.空间统计数据包含空间数据信息及其被访问的次数信息,先将空间数据信息映射成空间点云,空间数据的访问次数信息映射成点云向量,然后利用空间点云聚类梯度算法剔除偶发性访问形成的离散点,并通过空间聚类提取对空间统计数据进行压缩,同时给出了聚类梯度和聚类距离参数的选择方法.实验测试结果表明:算法能有效剔除偶发性访问形成的空间统计数据,且压缩率较高.
In order to improve the service quality of spatial statistics data transmission formed by mass spatial data access, a point cloud clustering algorithm for spatial statistical data in cloud computing environment is proposed. Spatial statistical data contains the spatial data information and the number of times it is accessed, The spatial data information is mapped into spatial point cloud and the information of spatial data is mapped into point cloud vector. Then the spatial point cloud clustering gradient algorithm is used to eliminate the discrete points formed by sporadic access, and the space statistics are extracted by spatial clustering Compression, at the same time gives the selection method of clustering gradient and clustering distance parameters.The experimental results show that the algorithm can effectively eliminate the spatial statistics formed by occasional visit, and the compression rate is high.