An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems,most spatial query predicates are consisted of topological relationships between spatial objects,and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multidimensional histogram and the transformation scheme. Proposed scheme applies two-partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.     

An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multidimensional histogram and the transformation scheme. Proposed scheme applies two-partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.     

A solution of spatial query processing and query optimization for spatial databases

Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.     

A solution of spatial query processing and query optimization for spatial databases

Recently,attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model,including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end,an implementation of this design is given in a spatial query subsystem.     

A solution of spatial query processing and query optimization for spatial databases

Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.     

有效支持空间OLAP的空间数据仓库模型研究

为了实现各类空间联机分析,提供更加全面灵活的空间决策支持,提出了一个空间数据立方体与空间索引结构相互协作的空间数据仓库模型,并同时构建了一个与之协作的空间索引结构aR^ B_tree．aR^ B_tree基于R^ _tree和B_tree实现,存储了空间维及时间维的聚集信息和层次关系,可以有效支持区域聚集查询．对各种空间联机分析操作进行了分类,分析表明该模型充分利用了传统数据仓库成熟的建模和联机分析技术,结合了空间索引结构在空间层次结构上的灵活特性,可以有效地支持各类空间联机分析．最后比较了aR^ B_tree与其他索引结构在区域聚集查询方面的性能．实验结果证明,在区域聚集查询中aR^ B_tree的节点访问次数和查询执行时间均小于现有索引结构．     

空间连接的选择性估计

空间连接是空间数据库中非常重要和耗时的操作，而空间连接的选择性估计对于查询优化器能否选择一个较好的执行计划至关重要。本文介绍了3种空间连接的选择性估计方法，并对其进行了比较分析。     

基于改进空间平滑技术的ESPRIT探地雷达时延估计算法

该文针对探地雷达地下回波时延估计问题,在详细论述ESPRIT探地雷达时延估计数据预处理过程的基础上,提出一种基于改进空间平滑技术的ESRPIT探地雷达超分辨率时延估计算法。基于FDTD的层状模型仿真数据验证了所提算法的有效性和可靠性。     

基于空间平滑MUSIC算法的智能天线DOA估计方法

波达方向(DOA)估计是智能天线系统中的关键技术之一,在研究基于MUSIC算法的传统DOA估计的基础上,提出了一种基于空间平滑技术MUSIC算法的DOA估计方法。仿真结果表明,对于相干信源,采用空间平滑MUSIC算法,能够得到尖锐的谱峰和较高的分辨率。     

复参数最小二乘估计方法

提出了基于复数U-D分解的复参数最小二乘估计方法。在传统的加权遗忘因子法的递推算法中,方差矩阵P(k)由于衰减很快而极易失去正定性.为了保证参数估计的收敛性,利用复数U-D分解,将方差矩阵P(k)进行U-D分解,将P(k)矩阵的递推计算已转化为U(k)和D(k)的递推计算问题,保证了数值计算的稳定性.     

空间相关分析因素对储层建模中克里金估计结果的影响

研究采样数据的空间分布及合理地选择参数是得到符合真实地质情况的克里金估计结果的基础。利用某储层数据来研究空间相关分析的主要影响因素与克里金估计结果的直接关系 ,为正确使用这些参数提供参考。这些因素与参数包括采样点的位置分布特征、变差函数模型的块金效应、变差函数模型的变程、变差函数模型的类型、空间结构的各向异性和空间搜索范围。在分析每种因素影响的同时 ,给出了相应的实际数据估计的结果图。研究结果表明 ,距离估计点较近的采样点对估计结果的影响较大 ;主轴方向的采样点比垂直于主轴方向上的采样点对估计结果的影响大 ;搜索半径通常取 1.3～ 2倍的变程值。同时还认为 ,在大多数情况下应选用球状模型和指数模型 ,除非十分必要时使用高斯模型     

改进的半连接查询优化算法

在多关系连接查询中,普通半连接查询方法没有优化子查询的半连接顺序,导致查询代价较高,为此,本文提出了一种改进的半连接查询优化算法.首先,将多关系连接组织成较小代价的类树形结构,然后利用半连接操作对处于根节点处的关系进行最大化缩减,并以此为基础利用PERF位向量对其他节点进行缩减,最后回收缩减关系进行连接操作.模拟实验表明改进的半连接查询优化算法能够有效地缩减查询关系,降低查询代价.     

基于空间分析的矿产资源评价方法

根据矿产资源评价的特点,将GIS不同层次的空间分析方法应用于矿产资源评价中,通过对预测区的研究确定影响成矿的主要因素;运用GIS的图形分析确定参与评价的因子,生成各专题图层,建立专用的评价数据库;此外,运用层次分析建模方法确定了各因子权重,建立基于层级权重叠加模型的评价方法,实现了与GIS系统的集成,并最终圈定成矿预测靶区.实践结果表明将GIS技术应用于矿产资源评价不仅拓展了GIS的应用领域,而且改变了传统的矿产资源评价方法,为矿产资源评价提供了新的思路和手段.     

视频数据存储方式及运动估计算法的内存访问效率

通过分析常用运动估计算法的内存访问模式,揭示出他们在通用计算机和数字信号处理器上使用时存在的效率问题,以及造成此问题的原因,并提出一种新的内存访问效率高的视频数据存储方式即叠瓦式存储方式。研究结果表明:使用新的视频数据存储方法,解决了跨缓存线访问数据的问题,并显著降低了运动估计过程中的高速缓存跑靶率;对全搜索算法,在算法本身不做任何改动的情况下,其运动估计过程速度提高28%。因此,叠瓦式存储方式的使用,可以有效地加速运动估计过程。     

Spatial aggregations for spatial based decision making in spatial data warehouses

For spatial based decision making such as choice of best place to construct a new department store, spatial data warehousing system is required more and more previous spatial data warehousing systems; however, provided decision making of non-spatial data on a map and so those cannot support enough spatial based decision making. The spatial aggregations are proposed for spatial based decision making in spatial data warehouses. The meaning of aggregation operators for applying spatial data was modified and new spatial aggregations were defined. These aggregations can support hierarchical concept of spatial measure. Using these aggregations, the spatial analysis classified by non-spatial data is provided. In case study, how to use these aggregations and how to support spatial based decision making are shown.     

Spatial aggregations for spatial based decision 

For spatial based decision making such as choice of best place to construct a new department store, spatial data warehousing system is required more and more previous spatial data warehousing systems; however, provided decision making of nonspatial data on a map and so those cannot support enough spatial based decision making. The spatial aggregations are proposed for spatial based decision making in spatial data warehouses. The meaning of aggregation operators for applying spatial data was modified and new spatial aggregations were defined. These aggregations can support hierarchical concept of spatial measure. Using these aggregations, the spatial analysis classified by nonspatial data is provided. In case study, how to use these aggregations and how to support spatial based decision making are shown.     

Scale-based spatial data model for GIS

Being the primary media of geographical information and the elementary objects manipulated, almost all of maps adopt the layer-based model to represent geographic information in the existent GIS. However, it is difficult to extend the map represented in layer-based model. Furthermore, in Web-Based GIS, It is slow to transmit the spatial data for map viewing. In this paper, for solving the questions above, we have proposed a new method for representing the spatial data. That is scale-based model. In this model we represent maps in three levels: scale-view, block, and spatial object, and organize the maps in a set of map layers, named Scale-View, which associates some given scales. Lastly, a prototype Web-Based GIS using the proposed spatial data representation is described briefly.     

Scale-based spatial data model for GIS

Being the primary media of geographical information and the elementary objects manipulated, almost all of maps adopt the layer-based model to represent geographic information in the existent GIS. However,it is difficult to extend the map represented in layer-based model. Furthermore,in Web-Based GIS,It is slow to transmit the spatial data for map viewing. In this paper,for solving the questions above,we have proposed a new method for representing the spatial data. That is scale-based model. In this model we represent maps in three levels：scale-view,maps in a set of map layers,named Scale-Lastly,a prototype Web-Based GIS using described briefly.     

XML查询优化的面向路径可扩展模型

通过XQuery中的路径表达式的处理提出了一种更为完整和灵活的查询优化模型,称之为POEM(面向路径的可扩展模型)．与现有的解决方案不同,模型先给出路径表达式的形式化描述——查询路径图,并根据路径表达式查询中影响性能的关键因素——结构连接建立了POEM查询优化模型．然后作了原始查询和经过POEM优化后查询的性能比较．     

红树林景观空间结构分析方法

红树林是一种分布于潮间带的特殊森林,其生态系统与陆地生态系统无论在功能、作用,还是在物质和能量交换机制等方面都存在着很大的差异。为了探讨更适用于红树林景观空间结构的分析方法,笔者从红树林功能和作用方面,尤其是其消浪护岸作用的角度,讨论了海湾内理想的红树林空间分布,在此基础上定义了红树林丰度、空间分布均匀度、红树林岸线长度比例、高效护岸红树林面积比例4个红树林景观空间结构分析指标,介绍了根据红树林和海岸线空间分布图通过空间叠置分析计算这些指标的方法,并利用此方法对广西珍珠港、茅尾海和铁山港的红树林空间结构进行了分析。结果表明:这4个指标不但与红树林数量有关,也与其空间分布状态(斑块位置、形状、大小)以及与海岸线长度和空间位置有关,反映了红树林在海湾内的空间结构状态,既可用于同一时期不同海湾红树林数量的比较分析,也可用于同一海湾不同年度红树林数量的比较分析,并可对红树林景观空间结构进行优化。