1) neighbor-finding
邻域查询
1.
Fast neighbor-finding algorithm based on linear quadtree;
基于线性四叉树的快速邻域查询算法
2.
In this paper, we refer to the neighbor-finding technologies based on quad tree and octree.
邻域查询技术是地理信息系统中基本的空间分析操作,本文对基于四叉树和八叉树的邻域查询技术进行了探讨,并详细介绍了基于显式四叉树和FD线性四叉树的邻域查询算法。
2) nearest neighbor query
近邻查询
1.
According to the abstract degree, nearest neighbor query has three main categories: nearest neighbor query between point and point, nearest neighbor query between point and line segment, and nearest neighbor query between line segment and line segment.
空间数据库的近邻查询近几年受到人们越来越多的关注。
2.
In this paper we proposed a new method,dimensionality reduction with DCT,and further provided the method of similarity search about range query and nearest neighbor query.
提出了一种新的方法,利用离散余弦变换(DCT)进行维归约,并在此基础上给出了对时序数据进行范围查询和近邻查询的相似性搜索方法。
3) range query
区域查询
1.
Experimental results show that not only can CMD-Forest support bulk appending efficiently but also provide higher range query performance.
它不但可以有效地支持数据仓库上的大数据量批量追加更新,而且具有很高的区域查询性能。
2.
Both of the range query and update costs of HDC are O(logdn), and the overall cost is O((logn)2d) (.
区域查询是数据仓库上支持联机分析处理(o0n)-lineanalyticalprocessing,简称OLAP)的重要操作。
4) Realm name inquiring
域名查询
5) nearest neighbor queries
最近邻查询
1.
The algorithm efficiently solves reverse nearest neighbor queries for continuously moving points in the plane.
为研究动态环境下解决反向最近邻查询的算法,采用TPR-树索引结构给出了解决动态环境下的最近邻查询算法,并提出反向最近邻查询算法。
6) k-NN query
k邻近查询
1.
k-NN query based on multi-autonomous spatial data source is widely used in spatial information realm.
多自治空间数据源的k邻近查询处理在空间信息领域具有广泛的应用。
补充资料：超导电性的局域和非局域理论（localizedandnon-localizedtheoriesofsuperconductivity）
超导电性的局域和非局域理论（localizedandnon-localizedtheoriesofsuperconductivity）
伦敦第二个方程（见“伦敦规范”）表明，在伦敦理论中实际上假定了js(r)是正比于同一位置r的矢势A(r)，而与其他位置的A无牵连；换言之，局域的A(r)可确定该局域的js(r)，反之亦然，即理论具有局域性，所以伦敦理论是一种超导电性的局域理论。若r周围r'位置的A(r')与j(r)有牵连而影响j(r)的改变，则A(r)就为非局域性质的。由于`\nabla\timesbb{A}=\mu_0bb{H}`，所以也可以说磁场强度H是非局域性的。为此，超导电性需由非局域性理论来描绘，称超导电性的非局域理论。皮帕德非局域理论就是典型的超导电性非局域唯象理论。
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