快速动态优先搜索树的实现及其应用

对形如（x1：x2,[-∞：y]）的二维查询问题,提出一种快速的、易于实现的动态优先搜索树数据结构及其相关算法,采用只在叶节点存储数据的结构,以及在常数时间内实现旋转操作的算法。设n为数据点的个数,k为满足搜索条件的解的个数,则该动态搜索树空间复杂度为O（n）,插入、删除操作的时间复杂度为O（10gn）,搜索复杂度为O（logn＋k）。     

基于有向项集图的频繁集挖掘优化算法

关联规则挖掘是数据挖掘研究中一个非常重要的研究领域。文章利用有向项集图(DISG)来存储有关频繁项集的信息，提出了利用深度优先的策略进行搜索的频繁项集挖掘的优先算法UDBDG(Updated DFS Based DISG)。最后分析了算法在时间和空间上的复杂度并以mushroom数据库为例进行了试验。试验结果证明算法对于处理稠密集数据是有效的。     

基于向量的数据流滑动窗口中最大频繁项集挖掘*

针对相关算法在挖掘数据流最大频繁项集时所存在的问题,提出了一种基于向量的数据流滑动窗口中最大频繁项集挖掘算法。该算法首先用向量作为概要数据结构,采用定量更新滑动窗口策略解决时间粒度问题;其次通过位运算产生频繁项集,利用矩阵和数组存储辅助信息,深度优先搜索产生最大频繁项集时利用剪枝策略进一步减少挖掘时间;最后用索引链表存储挖掘结果以提高超集检测效率。理论分析和实验结果验证了该算法的有效性。     

基于粒计算的序决策规则提取算法

为了从序决策表中获取最简有序规则,在研究粒计算理论的基础上,提出一种基于粒计算的序决策规则提取算法.该算法通过定义有序矩阵、λ阶粒库的概念,利用粒计算的思想将序决策表转化为有序矩阵形式.并对有序矩阵及其对应的粒库进行分析推理,以规则覆盖度和置信度为搜索条件,尝试从较低阶的粒库中提取出尽可能多满足用户期望的最简有序规则.最后通过实例验证该算法的有效性.     

基于变精度粗集和搜索树的增量规则获取算法

基于可变精度粗糙集模型和搜索树提出了一种新的增量式规则获取算法。该算法引入可变精度粗糙集模型以已获取规则集为启发信息,通过对解空间进行深度优先启发式搜索产生新的不确定性规则;并通过对原有规则置信度的更新,给出了原有规则集的更新算法;最后给出了实例分析。     

一种适用于汉语的索引文件结构

本文给出一种以词语为索引项的索引文件存储结构,以及基于这种结构的索引查询算法.首先分析中文索引库的分布规律,接着在此基础上设计了一种逆序存储的三层索引结构,这种结构在创建索引时能根据词语频率自动调整存储顺序,最后给出一种基于自动机和逆向最大匹配的索引查询算法.实验系统TIFS将三层索引结构与B树、哈希方法在时间和空间复杂度方面进行对比,结果表明,对于大规模的中文文本检索,三层索引结构的综合效果最好.     

数据包过滤规则的快速匹配算法和冲突检测

通过分析数据包过滤技术中的性能瓶颈,提出了过滤规则的快速匹配算法BSLT．该算法采用Trie数据结构存储规则表,并只在叶节点存储相应规则,节省了存储空间,其空间复杂度为O(NW),查找的时间复杂度为O(W);在匹配时采用二分法进行查找,提高了匹配速度,匹配的时间复杂度为O(N)．实验证明BSLT的吞吐率在100条规则内比顺序匹配算法提高了近20％,而且规则越多．BSLT的优势越明显．此外,分析了数据包过滤技术的另一个问题——规则冲突,给出了冲突的理论证明和查找算法．实验证明该算法能准确地检测出冲突规则．     

一种高效的图像数据库检索方法

对于大型图像库,如何高效地检索出相似图像是图像检索系统的一大挑战。提出了一种改进的K-均值聚类算法建立分层结构的索引,再利用A*树算法和三角不等式原则及N近邻方法对索引库快速高效地搜索,达到对图像库快速高效检索相似图像的目的。实验在Corel图像库上进行,实验结果表明该方法以对数时间复杂度实现基于内容的高效检索。     

复合并行机排序问题的启发式算法研究

为有效解决复合并行机排序的极小化最大完成时间问题,提出了分支定界算法和改进的启发式动态规划算法。利用分支定界算法的3个工具:分支模型、边界和优先规则,构建出分支搜索树。按优先规则进行定界搜索,从而减小了问题求解规模。将原始作业转换为虚拟作业,根据Johnson法则,求解出原问题的最优排序。改进的动态规划算法复杂度分析和计算实验表明,这两个算法可靠性高并且可以解决实际问题。     

港区导航系统中最短路径搜索算法

分析Dijikstra算法、限制区域搜索算法以及A*算法的时间复杂度和空间复杂度,提出一种最短路径搜索算法。将静态存储和动态搜索相结合,以限定区域搜索算法为主、A*算法为辅,并根据港区路况实现该算法。实验结果表明,在区域路网结构相对比较规则的情况下,该算法能够提高路径搜索的效率。     

用于控制器保护的防火墙规则的三叉树算法

为提高防火墙安全规则的查找速度,提出了一种面向IP地址集合处理的时间复杂度为O([log32N])的三叉树查找算法,N为安全规则数。用空间分析法解决规则冲突,并给出规则树的生成算法,该方法适用于控制应用的可靠性分析和安全完整性等级验证的要求。     

Generation of t-ary trees with Ballot-sequences*

We define Ballot-sequences for t-ary trees based on the ideas of Ballot-sequences of binary trees presented by Rotem. Later an efficient algorithm for the generation of t-ary trees with Ballot-sequences in B-order is presented. The algorithm generates each sequence in constant average time O(1), and the sequences are generated in lexicographical order. The ranking and unranking algorithms with O(tn) time complexity are also described.     

On the max-entropy rule for a binary search tree

Summary A modified max-entropy rule is proposed for constructing nearly optimum binary search tree in the case of ordered keys with given probabilities. The average cost of the trees obtained by this rule is shown to be bounded by the entropy of the probability distribution plus a constant not larger than one. An algorithm for implementing this rule is then suggested and its complexity is investigated in a probabilistic setting.     

Dealing with Satisfiability and n-ary CSPs in a Logical Framework

We investigate in this work a generalization of the known CNF representation that we call General Normal Form (GNF) and extend the resolution rule of Robinson to design a new sound and complete resolution proof system for the GNF. We show that by using a cardinality operator in the GNF we obtain the new representation CGNF that allows a natural and efficient Boolean encoding for n-ary finite discrete extensional CSPs. We prove that the space complexity of a CSP encoded in the CGNF is identical to its space complexity when it is expressed in the classical CSP representation. We prove that the generalized resolution rule applies for the CGNF encoding and introduce a new inference rule whose application until saturation achieves arc-consistency in a linear time complexity for n-ary CSP expressed in the CGNF encoding. Two enumerative methods for solving CSP instances encoded in this Boolean framework are studied: the first one (equivalent to MAC in CSPs) maintains full arc-consistency at each node of the search tree while the second (equivalent to FC in CSPs) performs partial arc-consistency on each node. Both methods are experimented and compared on some instances of the Ramsey problem, randomly generated 3/4-ary CSPs and promising results are obtained. We also adapted the notion of clause learning defined in SAT for the CGNF encoding. Finally, we show how the proposed inference rule can be used to achieve Path-consistency in the case of binary CSPs encoded in CGNF, and how it can be used to enforce strong path consistency when it is combined with the generalized resolution rule.     

故障树模块化在装甲车辆灭火系统故障诊断中的应用

为了实现装甲装备灭火系统故障的快速诊断,提出了一种故障树模块化分析方法;对灭火系统故障树进行深度优先最左遍历,并记录遍历过程,按照遍历顺序对故障树中的每个事件进行标定,并将灭火系统故障树划分为相互独立的模块,依据划分的模块可以通过故障现象对模块内的故障进行排查及修复;实验结果分析表明,该方法可以快速修复模块故障,恢复系统功能,简化了以往对灭火系统所有子事件遍历查错的繁琐过程。该方法同样可以计算故障模块的失效概率,并可以实现故障模块的整体更换,恢复系统性能;证明了故障树模块化方法在灭火系统故障诊断中具有较高的效率,简化了灭火系统诊断流程,在装甲车辆其他系统故障诊断中具有借鉴作用,符合现代作战对于装备保障的需求。     

基于归约的柔性工艺过程模型

该文提出了一种基于“与/或”归约的柔性工艺表达模型,为实现工艺过程动态设计与生产规划提供了一种新的技术方法。同时,详细描述了柔性工艺归约的有序搜索的算法,其中,宽度算法用来进行寻找可替代的工序、加工方法或设备,可拓宽工艺的柔性;深度算法用来进行工艺的可加工性设计和设备的负荷总体平衡,可预防决策短见。     

基于CDFG的SoC验证方法及其分割与搜索算法

随着芯片复杂度以及市场对集成电路上市时间要求的不断提高,对SoC设计方法和验证方法带来了巨大的挑战。控制数据流图可用于系统建模、软硬件功能划分、系统综合与验证等多个环节。该文针对SoC验证的需要,利用CDFG,研究了基于CDFG的验证体系,给出了CDFG的几种定义,讨论了CDFG的表示方法,提出了基于CDFG的验证流程,研究了基于DFS的生成树算法、CDFG的分割算法和CDFG的搜索算法,并以实例说明了这些算法在验证流程中的作用。     

A decision tree approach to graph and subgraph isomorphism detection

A new approach to the problem of graph and subgraph isomorphism detection from an input graph to a database of model graphs is proposed in this paper. It is based on a preprocessing step in which the model graphs are used to create a decision tree. At run time, subgraph isomorphisms are detected by means of decision tree traversal. If we neglect the time needed for preprocessing, the computational complexity of the new graph algorithm is only polynomial in the number of input graph vertices. In particular, it is independent of the number of model graphs and the number of edges in any of the graphs. However, the decision tree is of exponential size. Several pruning techniques which aim at reducing the size of the decision tree are presented. A computational complexity analysis of the new method is given and its behavior is studied in a number of practical experiments with randomly generated graphs.     

基于单元树结构的广度优先P2P搜索算法

提出基于单元树结构的广度优先搜索算法UTBFS。将单元树结构生成算法与广度优先算法相结合,阐述UTBFS的实现思路,对其时间复杂度、空间复杂度、可行性、优越性进行分析。实验仿真结果显示,相比于传统的广度优先搜索算法和随机广度优先搜索算法,UTBFS减少了需要转发消息的邻居节点个数和冗余消息,因此性能更优。     

Embedding ofk-ary Complete Trees into Hypercubes with Uniform Load

The main result of this paper is an algorithm for embeddingk-ary complete trees into hypercubes with uniform load and asymptotically optimal dilation. The algorithm is fully scalable—the dimension of the hypercube can be chosen independent of the arity and height of the tree. The embedding enables to emulate optimally both Divide&Conquer computations onk-ary complete trees where only one level of nodes is active at a time and general computations based onk-ary complete trees where all tree nodes are active simultaneously. As a special case, we get an algorithm for embedding thek-ary complete tree of given height into its optimal hypercube with load 1 and asymptotically optimal dilation.