共查询到19条相似文献,搜索用时 609 毫秒
1.
基于路由机制的时变路网k近邻算法 总被引:1,自引:1,他引:0
针对现实生活中动态路网的地理信息查询问题,提出了一种基于路由机制的动态路网中k近邻查询的算法。其主导思想是利用空间换时间,用路由表保存历史查询结果,用查询路由表的方法代替传统的最短路径计算,通过历史数据减少系统重复计算并对车辆行驶路径进行规划,用更新路由表的方法适应路况的变化。围绕路由表这一核心,改进相应的k近邻算法的过滤、精炼过程。通过路由表对动态路网进行少量的预处理,减少系统在k近邻搜索中的候选点数量,缩小查询范围,提高搜索效率。 相似文献
2.
路网中互近邻查询处理方法 总被引:1,自引:0,他引:1
提出路网中的互近邻查询问题.给定路网G(V,E),对象集P,查询点q,近邻数k1和k2,互近邻查询返回既是q的k1近邻,又是q的反k2近邻的对象集.为解决该问题,首先提出基础算法,即先求出查询点q的k1近邻作为候选,再验证这些候选是否为真正的结果.然后,在此基础上提出了优化算法,根据落在对象点与查询点最短路径边上的标记点个数直接排除掉一些错误的候选对象.最后,通过实验验证了优化算法的有效性. 相似文献
3.
通过分析已有的索引结构在进行k近邻查询时效率上的不足,提出了适合进行k近邻查询的X*树索引结构,采用了新的结点分裂算法,同时不需要额外存储结点分裂的历史信息。实验结果表明它比X树的时间和空间性能更好,更适合k近邻查询的应用。 相似文献
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连续k近邻查询(continuous k-nearest neighor,Ck NN)定义为查找指定路径上每个点的k个最小代价数据对象。目前关于Ck NN的研究都是在欧式空间与静态路网中实现的,这些算法不能直接应用到边权值变化的时间依赖路网中。定义并解决了时间依赖路网中的Ck NN问题,利用积分的性质以及通过对权值代价函数合并的方式提出了两阶段的基于分割点的Ck NN查询算法。过滤阶段提出了计算节点到达时间的方法,再利用到达时间查询出多个候选k近邻结果;求精阶段将查询点到候选结果的权值函数合并,通过计算函数交点得到分割点,进而为查询返回若干个分割点以及相应区间内的k近邻结果。实验结果表明,与进行多次快照k近邻查询相比,所提算法在响应时间上减少了近一个数量级。 相似文献
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提出一种路网中查询点速度不确定的连续k近邻查询方法.查询点在起始位置向服务器提出查询请求,得到k近邻的候选集.随着查询点的移动,利用有效候选集计算当前的k近邻,而不必再向服务器请求,从而减少了服务器计算代价.当候选集部分失效时,由服务器返回候选集中失效的兴趣点的当前信息,使候选集有效.当候选集完全失效时,由查询点重新向服务器提出查询请求,得到新的候选集.并提出一种计算候选集的优化方法,降低了查询代价.最后,通过实验验证了所提算法的有效性. 相似文献
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提出一种道路网络中针对两种不同类型目标点的k组路径最近邻居查询,这是一种新的查询:给出用户希望到达的终点位置以及两组目标点集合,这种查询返回连接用户当前位置和终点位置的最短路径,以及相对于这条最短路径的k组路径最近邻居,每组包含两个不同类型的目标点,将这种查询命名为k-PNNT.提出了一种典型的过滤-精炼算法得到k-PNNT及对应的最短路径,并且在实际道路网络中进行了实验.实验证明,算法可行,有效. 相似文献
9.
在充分认识到k阶Voronoi图在解决连续k个近邻查询优越性和现实不可行性的基础上,用分支限界的思想去界定预创建Voronoi图生成点范围的上界,提出了一种动态地创建局部Voronoi图的办法解决连续近邻查询问题。该方法只是在给定查询段上所有点的k个近邻范围上界内创建一个局部的k阶Voronoi图,这样大大降低了基于Voronoi图的连续k近邻查询的代价。 相似文献
10.
连续近邻查询方法的研究 总被引:3,自引:0,他引:3
连续近邻查询(CNN)要检索一给定查询线段上每一点的近邻。它是时空数据库中一种重要的查询类型,在智能交通系统中有着广泛的应用。Voronoi图解决连续近邻查询问题,思想简单明晰,但Voronoi图构造代价太高,尤其是高阶的Voronoi图。本文从文献得到启示:用分枝限界的思想去界定预创建Voronoi图生成点范围的上限。提出了一种动态地创建局部Voronoi图的办法解决连续近邻查询问题。这种方法只是在给定查询段上所有点的k个近邻范围上限内创建一个局部的k阶Voronoi图,这样会大大降低基于Voronoi图的连续k近邻查询的代价。 相似文献
11.
Optimization and evaluation of shortest path queries 总被引:1,自引:0,他引:1
Edward P. F. Chan Heechul Lim 《The VLDB Journal The International Journal on Very Large Data Bases》2007,16(3):343-369
We investigate the problem of how to evaluate efficiently a collection of shortest path queries on massive graphs that are
too big to fit in the main memory. To evaluate a shortest path query efficiently, we introduce two pruning algorithms. These
algorithms differ on the extent of materialization of shortest path cost and on how the search space is pruned. By grouping
shortest path queries properly, batch processing improves the performance of shortest path query evaluation. Extensive study
is also done on fragment sizes, cache sizes and query types that we show that affect the performance of a disk-based shortest
path algorithm. The performance and scalability of proposed techniques are evaluated with large road systems in the Eastern
United States. To demonstrate that the proposed disk-based algorithms are viable, we show that their search times are significant
better than that of main-memory Dijkstra's algorithm. 相似文献
12.
最佳排序路径查询,是智能交通中的热点问题.在实际的应用中,由于最佳排序路径查询有许多限制条件,现有的算法不能有效地解决动态网络中受限制的路径查询问题.为了解决动态网络中最佳排序路径查询问题,用规则表示每个限制条件,提出了一种新的最佳排序路径查询形式,即多规则的最短路径查询.提供了统一的框架,该框架包含了路径集合查询和最短路径查询.在路径集合查询部分,为了高效地查询出满足多规则的路径集合,在广义规则树的基础上,提出一种新的树的遍历方式,即树的继承全遍历;并基于树的继承全遍历思想,提出一种剪枝技术,对路径集合进行删减,最后求得候选路径集合.在最短路径查询部分,提出一种基于动态阈值的最短路径搜索方法.通过两个真实的动态道路网络的实验验证,所提出的算法能够高效地解决多规则的最短路径查询问题. 相似文献
13.
Ke Deng Xiaofang Zhou Heng Tao Shen Qing Liu Kai Xu Xuemin Lin 《The VLDB Journal The International Journal on Very Large Data Bases》2008,17(5):1101-1119
A spatial k-NN query returns k nearest points in a point dataset to a given query point. To measure the distance between two points, most of the literature
focuses on the Euclidean distance or the network distance. For many applications, such as wildlife movement, it is necessary
to consider the surface distance, which is computed from the shortest path along a terrain surface. In this paper, we investigate
the problem of efficient surface k-NN (sk-NN) query processing. This is an important yet highly challenging problem because the underlying environment data can be
very large and the computational cost of finding the shortest path on a surface can be very high. To minimize the amount of
surface data to be used and the cost of surface distance computation, a multi-resolution surface distance model is proposed
in this paper to take advantage of monotonic distance changes when the distances are computed at different resolution levels.
Based on this innovative model, sk-NN queries can be processed efficiently by accessing and processing surface data at a just-enough resolution level within
a just-enough search region. Our extensive performance evaluations using real world datasets confirm the efficiency of our
proposed model. 相似文献
14.
Alternative Solutions for Continuous K Nearest Neighbor Queries in Spatial Network Databases 总被引:2,自引:0,他引:2
Continuous K nearest neighbor queries (C-KNN) are defined as finding the nearest points of interest along an enitre path (e.g.,
finding the three nearest gas stations to a moving car on any point of a pre-specified path). The result of this type of query
is a set of intervals (or split points) and their corresponding KNNs, such that the KNNs of all points within each interval
are the same. The current studies on C-KNN focus on vector spaces where the distance between two objects is a function of
their spatial attributes (e.g., Euclidean distance metric). These studies are not applicable to spatial network databases
(SNDB) where the distance between two objects is a function of the network connectivity (e.g., shortest path between two objects).
In this paper, we propose two techniques to address C-KNN queries in SNDB: Intersection Examination (IE) and Upper Bound Algorithm
(UBA). With IE, we first find the KNNs of all nodes on a path and then, for those adjacent nodes whose nearest neighbors are
different, we find the intermediate split points. Finally, we compute the KNNs of the split points using the KNNs of the surrounding nodes. The intuition behind UBA is that
the performance of IE can be improved by determining the adjacent nodes that cannot have any split points in between, and
consequently eliminating the computation of KNN queries for those nodes. Our empirical experiments show that the UBA approach
outperforms IE, specially when the points of interest are sparsely distributed in the network. 相似文献
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最短路径查询是图数据管理中非常重要的一类问题.研究了基于规则的最短路径查询,它是一类特殊的最短路径查询问题.给定起点和终点,基于规则的最短路径查询是指找到一条从起点到终点的最短路径,使得此路径经过用户指定点集中的所有点,并且某些点的访问顺序满足一定的偏序规则.该问题被证明是一个NP-hard问题.目前已有的工作侧重于空间数据集(两点之间的最短距离用欧氏距离表示)上基于规则的最短路径问题,它采用穷举的方式列出所有满足规则的路径,然后选择长度最小的路径作为问题的解.然而在实际的道路交通网中,两点之间的距离等于两点之间的最短路径的长度,它往往大于两点之间的欧氏距离;此外,采用穷举的方式会造成大量重复的计算.因此,设计了一种前向搜索算法以及一些优化技术来求解该问题.最后,在不同的真实数据集上设计了大量的实验来验证算法的有效性.实验结果表明,该算法可以快速给出问题的解,而且算法的效率在很大程度上超过了现有的算法. 相似文献
17.
提出一种用于公交路线规划的最优路径查询方法.利用最优位置选择思想,在给定源点和终点的路网中找到k最短路径中最优性值最大的路径,即客流量最大的路径,为进行公交路线规划提供参考.采用k最短路径算法找到长度满足条件的k最短路径,然后对这k最短路径上的一些特殊顶点(如路口)进行最优性查询,从而找到k最短路径中最优性值最大的路径.最后,通过实验验证该方法的有效性. 相似文献
18.
空间数据库的多类型最近邻查询逐渐受到人们的关注,关于K最近邻查询的研究也较多,但多类型K最近邻查询的研究还存在空白。针对道路网络中的多类型K-最近邻(MT-KNN)问题,结合多类型最近邻查询及K最近邻查询的理论,提出了多类型K最近邻查询算法。通过对分层编码视图进行扩展,建立了多路径分层编码视图,并利用逐步扩展局部路径的方法,实现了多类型K最近邻查询,实验结果分析表明算法具有较好的性能。 相似文献
19.
An efficient path computation model for hierarchically structured topographical road maps 总被引:4,自引:0,他引:4
《Knowledge and Data Engineering, IEEE Transactions on》2002,14(5):1029-1046
In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel shortest path algorithm named ISPAH. Experimental results show that inter query shortest path problem provides more opportunity for scalable parallelism than the intra query shortest path problem. 相似文献