1) SIMG-R tree
SIMG-R树
1.
This paper introduces the core idea of SIMG, and the authors proposed a new spatial data index method-SIMG-R tree spatial Index based on the features of the traditional spatial indexing technology and the new representation method in SIMG, which can be used for searching for SIMG geometry quickly.
空间信息多极网格(SIMG)是一种适合网格计算环境下空间信息表示的新方法,介绍了SIMG的核心思想及其空间数据组织原理,基于现有空间索引技术和SIMG相对量表达特点,提出了一种SIMG-R树空间索引技术,可实现SIMG细部地物的快速查询。
2) R-tree
R树
1.
R-tree spatial join algorithm based on the breath-first paradigm;
一种基于广度优先策略的R树连接算法
2.
Multi-scale spatial index structure based on R-tree;
一种用于多分辨空间数据的R树索引结构
3.
Brand-new node-choosing algorithm of R-tree spatial index;
一种全新的R树节点选择算法
3) R tree
R树
1.
In terms of the mobility of data set, global distances at different situation are refined and some heuristics are presented for data set indexed by data structure of R tree family.
根据数据对象集的运动性不同,精化了运动和静止数据集下的全局距离的定义,并对R树结构索引的数据集给出了裁减、更新和访问启发式规则。
4) R*-tree
R*-树
1.
Optimization research of spatial index structure of R*R*-tree;
R*-树空间索引的优化研究
2.
This paper from the features of different index structure analyzes the reverse nearest neighbor query superiorities under low dimension based on R*R*-tree and puts forward a new kind reverse nearest neighbor query method about spatial.
反最近邻查询是在最近邻查询基础上提出的一种新的查询类型,是空间数据库的应用拓展,在不同维数下,根据不同的索引结构,反映出空间对象的反最近邻查询差异性较大,从不同索引结构的特性出发,分析了低维环境丁基于R*-树的反最近邻查询优势,提出高维环境下一种新的基于SRdann-树索引结构的空间对象反最近查询方法,优化了不同维数下空间对象的反最近查询性能,提高了查询效率。
5) R*-tree
R*树
1.
In spatial database application,to solve the problem that a single special indexing structure constrains retrieval performance with the increment of the amount of data,a hybrid tree special indexing structure is proposed,and so is OR*R*-tree,which is based on Octree and R*R*-tree in 3D GIS.
方法提出一种三维GIS中基于八叉树和R*树的混合树空间索引结构OR*树,该结构在对三维索引空间进行八叉划分的基础上应用R*树索引技术,将操作空间限定在某一特定的区域。
2.
According to the characteristics of Master Boot Record(MBR) in R*R*-tree, this paper creates the binary segment tree by sweeping the orthogonal overlapping region.
根据R*树节点硬盘主引导记录(MBR)特征,在不改变最小外包矩形特征的前提下,通过区域扫描对正交MBR重叠区域边界建立二叉线段树,以此为基础分别计算面积和周长,有效改善了R*树节点结构。
6) R-tree
R-树
1.
A dynamic R-tree index based on hybrid clustering algorithm;
基于混合聚类算法的动态R-树
2.
Region Matching Algorithm for DDM Based on Dynamic R-tree;
基于动态R-树结构的DDM区域匹配算法
3.
Research of optimal continuous nearest neighbor query algorithm based on R-tree;
基于R-树的连续最近邻查询算法优化研究
补充资料：海南龙血树（小花龙血树）
百合科Liliaceae
乔木状，高3-4m。叶聚生于茎和枝顶，几呈套叠状，长约70cm，抱茎，无柄。圆锥花序长约30cm，花序轴无毛或近无毛。分布于海南西南部，生于背风区的干燥砂土上。越南、柬埔寨也有分布。国家三级保护濒危种。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条