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Queries of nature neighbor objects on UnitsDelaunay structure in spatial database

机译:空间数据库中UnitsDelaunay结构上自然邻居对象的查询

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In recent years, the research on models of spatial relation computation can be divided into two types: the spatial relation among intersected entities and the spatial relation among the non-intersected entities. Currently, the latter is often used distance, direction and coordinate systems and other methods to study. But these quantitative methods are difficult to sympathize with human natural language understanding and space cognitive habits.rnNature neighbor relationship is a vital space relationship. It can answer such questions as "Which hospital are adjacent to the moving object?" "Which schools are adjacent to the McDonald's shop?" In this paper, we analyzed two methods to compute the nature neighbor relationships: Voronoi diagram method and Delaunay triangulation method. We found the main problems for applying these methods to spatial selection are the overall and repetitive calculation. In some basic theory: (ⅰ) Define function f in order to distinct different types of triangle. According to the different sources of thernnodes, the f is individually equal to 0, 1 and 2. And then the 3x3 matrix C is built on the f According to the different values of |C|, we can divide the triangles as three types: α, β, γ. (ⅱ) Taking into account that the triangles of type α is not entirely internal concave polygon, we divide the type α into type α and δ on the condition whether the polygon includes the focus of the triangle or not. Then the D(P) composed by Q includes four types of triangles: α, β, γ and δ. (ⅲ) Demonstrate that the space scope of Q in R~2 is equal to the space scope of triangle set T of type α in D(P) , reasoned out the complement of Q in R~2 is equivalence with the set {T_β∪T_γ∪T_δ} and the nature neighbor relationship canrnonly exist in the set {T_β∪T_γ∪T_δ}. (ⅳ) For β and γ-tyPe triangle we posed a subset of their sources and demonstrated the certainty in the context of natural subset of the space adjacent to the existing relationship, and regarded the space scope of every subset as a Unit, defined the structure of UnitsDelaunay and proposed the construction algorithm of thernUnitsDelaunay. For the Quad GridFile: (ⅰ) Respectively approximated the Units composed of β and γ-tyPe triangles byrntwo methods of MBR of MCR and MBR. (ⅱ) Demonstrated the completeness of the closure of the result set of point querying. (ⅲ) Taking into account the update of GridFile, we proposed the Quad GridFile index structure, i.e. the structure added into quad tree spatial partition, replacing the update of structure by the reconstruction of GridFile structure, which the space scope of GridFile is represented by every leaf node. We utilized the extraction of candidate set of point spatial selection and self-join spatial selection as the instances. In the environment of Oracle 9.2.1 and Eclipse 3.1, we accomplished the proposed structures and related algorithm. Finally, we gave illustrations of the experimental results.
机译:近年来,关于空间关系计算模型的研究可分为两类:相交实体之间的空间关系和非相交实体之间的空间关系。目前,后者经常被用于距离,方向和坐标系等方法的研究。但是这些定量方法很难同情人类的自然语言理解和空间认知习惯。自然邻居关系是至关重要的空间关系。它可以回答诸如“哪个医院与移动物体相邻?”之类的问题。麦当劳商店附近有哪些学校?在本文中,我们分析了两种计算自然邻居关系的方法:Voronoi图方法和Delaunay三角剖分方法。我们发现将这些方法应用于空间选择的主要问题是整体和重复计算。在一些基本理论中:(ⅰ)定义函数f以区分不同类型的三角形。根据节点的不同来源,f分别等于0、1和2。然后在f上建立3x3矩阵C根据| C |的不同值,我们可以将三角形分为三种类型: α,β,γ (ⅱ)考虑到类型α的三角形不完全是内部凹面多边形,在多边形是否包含三角形焦点的条件下,我们将类型α分为类型α和δ。然后,由Q组成的D(P)包括四种类型的三角形:α,β,γ和δ。 (ⅲ)证明R〜2中Q的空间范围等于D(P)中类型为α的三角形集合T的空间范围,推断出R〜2中Q的补数与集合{T_β等价∪T_γ∪T_δ}和自然邻居关系只能存在于集合{T_β∪T_γ∪T_δ}中。 (ⅳ)对于β和γ-tyPe三角形,我们摆放了它们的一个子集,并在与现有关系相邻的空间的自然子集的上下文中证明了确定性,并将每个子集的空间范围视为一个单位,定义了并提出了UnitsDelaunay的构造算法。对于Quad GridFile:(ⅰ)通过MCR和MBR的MBR的两种方法分别近似由β和γ型Pe三角形组成的单位。 (ⅱ)证明了点查询结果集的闭合性。 (ⅲ)考虑到GridFile的更新,提出了Quad GridFile索引结构,即添加到四叉树空间分区中的结构,通过重建GridFile结构来替代结构更新,其中GridFile的空间范围表示为每个叶节点。我们利用点空间选择和自连接空间选择的候选集的提取作为实例。在Oracle 9.2.1和Eclipse 3.1的环境中,我们完成了所提出的结构和相关算法。最后,我们给出了实验结果的说明。

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