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Realization of R-tree for GIS on hybrid clustering algorithm

机译:基于混合聚类算法的GIS R树的实现

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摘要

The characteristic of geographic information system (GIS) spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.
机译:地理信息系统(GIS)空间数据操作的特点是查询比插入和删除要频繁得多,因此提出了一种新的混合空间聚类方法,用于构建GIS空间数据的R树。根据聚类方法的聚合,使用R树来构造空间数据的规则和特征。 HCR树是使用HCR算法构建的R树。为了测试HCR算法的效率,该算法不仅应用于静态R树的数据组织,而且还应用于动态R树的节点拆分。结果表明,具有HCR的R树具有搜索效率高,磁盘访问量少等优点。

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