树型结构在题库系统中的应用

树型结构是一种重要的非线性结构。二叉树也是其中一种,如用它表示横向和纵向都需扩充的系统,就会使系统过于庞大,不利于系统高效使用。本文提出一个用多分支树型结构实现管理系统的算法,给出了关于树型结构的几种算法。树型结构具有能方便实现类型和内容分类等优点。     

树型结构在题库系统开发中的应用

文章以题库管理系统的开发为例,详细介绍了B/S三层架构中树型结构的设计和实现方式.提出了一种在浏览器中构建动态树型结构的解决方案,即使用TreeView控件、数据库和递归算法来实现动态树型结构,灵活方便地管理题库.最后重点介绍了递归算法、树结点定位展开等的程序实现.     

WSN中基于树型标号系统的分布式路由算法

针对无线传感器网络中数据中心存储的路由问题,提出一种基于树型标号系统的分布式路由算法。将网络中的节点组织成以参考节点为根的树型结构,通过比较目的节点标号与邻居节点标号,选择转发节点,实现数据路由。分析与仿真结果表明,该路由算法的空间开销较低、路由效率较高,并且生成的路径接近最短路径。     

网页树型结构快速加载大数据量数据的实现

利用树型结构进行数据组织,层次清晰、操作方便、用途广泛。介绍了一种基于VS.NET技术设计实现的大数据量树型结构数据的快速加载方法,通过一种改进的基于广度优先的算法,将树型数据按照一定的层次和需要,分散地加载于树型结构上,从而较好地解决了大数量的树型数据在网页上树型结构加载时效率低下、延迟较长的问题。该方法在实际应用中,取得了很好的效果。     

一种BOM的算法实现

ERP／MRPII系统设计必然牵涉到物料清单（Bill Of Matreial e.g.BOM）的设计与计算，BOM呈树型结构，一般在计算时采用通用的数据结构算法，通过前台函数或过程嵌套实现。笔者在实际ERP系统开发中探索和采用了一种新的BOM展开算法－－存储过程实现递归调用。     

Rough集中U/P的快速算法

针对目前计算Rough集中U/P算法需要重复扫描决策系统、不断地进行属性值比较和排序的缺点,提出了一种基于树型结构的不可区分关系树,通过不可区分关系树实现了计算U/P的快速算法.该算法只需扫描一次决策系统,并且也避免了不断地进行属性值比较和排序.经实验验证该算法较目前基于排序的U/P算法更快,而且算法实现更简洁.     

采用树型结构的多微处理机计算机的体系结构

本文介绍具有树型结构的多微处理机系统的体系结构,它是一种将数量不受限制的单片微处理机(模块)组织而成的大型通用计算机系统。指出,具有互连通路的树型结构特别优越,其有效带宽与微处理机数的对数成反比。采用一种称为X树的持殊树型结构作为研究的模型。这种系统能提供一种供控制、寻址和信息传送用的分级结构体系。探讨了多微处理机间的通讯网络,即高速的、字节并行的一组有异步信息交换现程的通讯链路。在X树系统中每一个结点由一个功能较强的微处理机、一个开关网络和一个专用的通讯控制器构成。还讨论了网络拓扑、寻径算法、寻址方案、信息格式等问题。     

基于地址空间转换的协同Protel系统

为解决Protel电子电路设计软件协同编辑的问题,提出一种基于地址空间转换思想的Co-Protel系统解决方案.给出适用于PCB文档的树型层级结构,改进原有的地址空间转换算法保证文档的一致性,通过透明适配层转换实现命令集和地址空间集的转换,给出系统整体框架和功能实现模块,并通过实验验证了系统可用性.     

基于树型结构的规则挖掘

树型结构在计算机领域中已得到广泛应用。本文分析了数据挖掘在树型结构中的应用,提出了基于相似度的规则挖掘算法和实现。通过先验相似度和后验相似度的计算,对树型结构进行分类,然后再进行规则提取,形成规则判定树。     

基于递归算法的树型结构图的设计与实现

公交集团运营组织与调度系统加快了公交集团信息化建设步伐,提高了其管理水平和效率。在系统中需要用树型图来体现公交集团的组织结构,利用递归算法、开发工具和数据库三者结合来生成公交集团从总公司到分公司再到车队的三级结构图,从而为后续各模块的实现打下了基础。     

基于DAG的拓扑排序改进算法及在BOM中的运用

文章讨论了传统的BOM防止嵌套错误算法和低层码计算的算法的实现过程。在分析算法的实现过程后对其原理进行评价的基础上,将BOM树结构和DAG图性质进行比较后对这两种算法进行改进,提出了一种蕴涵了拓扑排序思想的算法。最后编程实现了此算法的伪代码,该算法在实际运用中取得了明显的效果,减少了数据库系统资源的占用,大大提高了数据库的性能和响应能力。     

Performance analysis of partial-match search algorithms for BD trees

Database systems are becoming increasingly popular for answering queries. Partial-match search queries are an important class of queries in such a system. Several storage structures have been proposed to answer these queries efficiently. The BD tree is an example of such a storage structure. A previous study indicated that the k-d tree performance is better than that of the BD tree for partial-match search queries. A recent paper reported some improved algorithms. However, it is unclear whether the improved algorithms show the BD tree in a favourable light for partial-match search queries. This paper explores the performance of these algorithms and compares their performance to that of the k-d tree. Since the BD tree construction process uses some heuristics to make it a better balanced tree, this paper also evaluates the effect of these heuristics on the partial-match search algorithms. The major conclusions of this study are that the BD tree performance for partial-match search is better than that of the k-d tree when an improved algorithm is used for partial-match search, and only the DZ expression rearrangement heuristic has substantial effect on partial-match search performance.     

空间故障网络及其与空间故障树的转换

空间故障树是一种研究系统可靠性与影响因素关系的理论体系,用树型结构描述元件与系统之间的可靠性关系。但实际故障发生过程是复杂的,难以表示成树型结构,而更为广泛的是网状结构。因此,尝试将空间故障树中的树型结构转换为网络结构,进而形成空间故障网络。给出空间故障网络的定义、性质及其与空间故障树的转换方法。目的是将空间故障网络转换为空间故障树,以利用空间故障树已有研究结果。给出一般结构和多向环结构的空间故障网络,及其转换为空间故障树的方法。为使用空间故障树理论研究一般网络结构故障发生过程提供方法。     

加快排序文档的剪枝决策树和分块的方法

检索系统利用排名学习算法从训练集中产生一个排名模型。而减少检索数据需要的时间则是检索系统的一种重要研究方向。为了减少检索的时间,对排名模型的剪枝策略和缓存进行了研究。利用决策树的冗余特性和高速缓冲存储器,提出了剪枝决策树模型和分块算法。最后,在两个公开的数据集上进行了实验,主要关注了是否可以在不影响模型效果的条件下,提高排名模型的效率的问题。实验结果表明剪枝决策树模型和分块算法可以有效地减少每个查询的排名时间。     

一种基于佳点集遗传算法的QoS组播路由选择方法

QoS组播路由选择是通信网络多点路由优化问题的重要部分,已被证明是NP-complete问题。该文针对目前QoS路由算法中存在的一些问题提出了一种新的算法,其核心是佳点集遗传算法。该算法首先通过预处理简化问题,而后采用遗传算法求解:编码采用Prüfer树结构,变异和交叉概率自适应选择。仿真结果表明,该算法是有效的、稳定的,具有较强的实用性。     

A parallel evolving algorithm for flexible neural tree

In the past few decades, much success has been achieved in the use of artificial neural networks for classification, recognition, approximation and control. Flexible neural tree (FNT) is a special kind of artificial neural network with flexible tree structures. The most distinctive feature of FNT is its flexible tree structures. This makes it possible for FNT to obtain near-optimal network structures using tree structure optimization algorithms. But the modeling efficiency of FNT is always a problem due to its two-stage optimization. This paper designed a parallel evolving algorithm for FNT (PE-FNT). This algorithm uses PIPE algorithm to optimize tree structures and PSO algorithm to optimize parameters. The evaluation processes of tree structure populations and parameter populations were both parallelized. As an implementation of PE-FNT algorithm, two parallel programs were developed using MPI. A small data set, two medium data sets and three large data sets were applied for the performance evaluations of these programs. Experimental results show that PE-FNT algorithm is an effective parallel FNT algorithm especially for large data sets.     

Drawing dynamic trees

A tree-drawing algorithm that addresses the weaknesses of current approaches to constructing graphical user interfaces is presented. Present algorithms either do not let you draw tree nodes of varying shapes and sizes or they draw such trees in a way that does not produce trees as compact as they could be, which is especially important when diagramming a large system. Also, they cannot reuse layout information when the trees changes, so after every change the layout must be recomputed and the tree redrawn. The main difference between these traditional approaches and the author's approach is that his algorithm is more geometric. Unlike other algorithms, it uses an explicit representation of node and subtree contours, and it stores every contour as a polygon. It has three advantages over traditional algorithms. It allows one to draw trees with nodes of any polygonal shape compactly. The data structure supports insert and delete operations on subtrees. It is simple to implement, yet flexible     

An Efficient Method for Version Control of a Tree Data Structure

A new method for version controlling of a tree structure is presented. The key feature of the method is that the latest state of a tree is retained and other versions are constructed from it on request, and information on the change history of a node is maintaind in its parent node. Several algorithms for efficient manipulation of the tree have been developed, and it has been demonstrated that they correctly manipulate the tree. The performance of these algorithms has been compared with those of other tree-based methods, and found to be nearly optimal in all aspects of the comparison. © 1997 John Wiley & Sons, Ltd.