最小k-击中集问题的一个随机近似算法

Franco等给出一个基于平均度数的最小3-击中集问题的贪心算法,并给出算法返回击中集规模的上界.首先将其算法推广成为求解最小k-击中集问题的贪心算法HGREEDY1(A,C),并类似地给出算法返回击中集规模的上界;然后给出基于最大度数的贪心算法HGREEDY2(A,C),并证明算法HGREEDY2(A,C)在给定条件下返回的击中集规模上界优于算法HGREEDY1(A,C);另外设计了用于求解最小k-击中集的随机算法RH(A,C),并对其性能进行平均分析;在此基础上设计一个求解最小k-击中集的随机近似算法并讨论其性质.     

Complexity Control of H.264/AVC Based on Mode-Conditional Cost Probability Distributions

A computational complexity control algorithm is proposed for an H.264 encoder running on a processor/power constrained platform. This new computational complexity control algorithm is based on a macroblock mode prediction algorithm that employs a Bayesian framework for accurate early skip decision. Complexity control is achieved by relaxing the Bayesian maximum-likelihood (ML) criterion in order to match the mode decision threshold to a target complexity level. A feedback algorithm is used to maintain the performance of the algorithm with respect to achieving an average target complexity level, reducing frame by frame complexity variance and optimizing rate-distortion performance. Experimental results show that this algorithm can effectively control the encoding computational complexity while maintaining a good rate-distortion performance at a range of target complexity levels.      

增量式CURE聚类算法研究

聚类是一种非常有用的数据挖掘方法 ,可用于发现隐藏在数据背后的分组和数据分布信息 .目前已经提出了许多聚类算法及其变种 ,但在增量式聚类算法研究方面所作的工作较少 .当数据集因更新而发生变化时 ,数据挖掘的结果也应该进行相应的更新 .由于数据量大 ,在更新后的数据集上重新执行聚类算法以更新挖掘结果显然比较低效 ,因此亟待研究增量式聚类算法 .通过对 CURE聚类算法的改进 ,提出了一种高效的增量式 CU RE聚类算法 .它能够很好的解决传统聚类算法在伸缩性、数据定期更新时所面临的问题 .实验结果显示本算法是一种有效的增量式聚类算法     

Sorting by Short Block-Moves

Sorting permutations by operations such as reversals and block-moves has received much interest because of its applications in the study of genome rearrangements and in the design of interconnection networks. A short block-move is an operation on a permutation that moves an element at most two positions away from its original position. This paper investigates the problem of finding a minimum-length sorting sequence of short block-moves for a given permutation. A 4/3 -approximation algorithm for this problem is presented. Woven double-strip permutations are defined and a polynomial-time algorithm for this class of permutations is devised that employs graph matching techniques. A linear-time maximum matching algorithm for a special class of grid graphs improves the time complexity of the algorithm for woven double-strip permutations. Received June 1, 1997; revised July 25, 1998.     

概率构造算法与遗传算法融合的可重构计算系统硬件任务划分

提出一种概率构造算法与遗传算法融合的算法,通过引入表示划分结果多样性的度量方法,利用概率构造算法产生具有多样性的较优的初始群体,并在此基础上利用遗传算法寻求最优解.实验结果表明,该算法能够获得比已有的基于列表的划分算法更优的划分结果,比采用完全随机初始群体的遗传算法缩短了运行时间.     

一种不用大小比较的快速模乘算法

基于Ｂｌａｋｌｅｙ算法,介绍了一种计算Ａ＊ＢＭＯＤＮ（Ｎ〉５００位）的迭代算法,在该算法中,不需要进行任何大小比较操作,该算法与Ｂｌａｋｌｅｙ算法相比其速度提高了一倍。     

Discovering the suitability of optimisation algorithms by learning from evolved instances

The suitability of an optimisation algorithm selected from within an algorithm portfolio depends upon the features of the particular instance to be solved. Understanding the relative strengths and weaknesses of different algorithms in the portfolio is crucial for effective performance prediction, automated algorithm selection, and to generate knowledge about the ideal conditions for each algorithm to influence better algorithm design. Relying on well-studied benchmark instances, or randomly generated instances, limits our ability to truly challenge each of the algorithms in a portfolio and determine these ideal conditions. Instead we use an evolutionary algorithm to evolve instances that are uniquely easy or hard for each algorithm, thus providing a more direct method for studying the relative strengths and weaknesses of each algorithm. The proposed methodology ensures that the meta-data is sufficient to be able to learn the features of the instances that uniquely characterise the ideal conditions for each algorithm. A case study is presented based on a comprehensive study of the performance of two heuristics on the Travelling Salesman Problem. The results show that prediction of search effort as well as the best performing algorithm for a given instance can be achieved with high accuracy.     

Road Detection and Tracking from Aerial Desert Imagery

We present a fast, robust road detection and tracking algorithm for aerial images taken from an Unmanned Aerial Vehicle. A histogram-based adaptive threshold algorithm is used to detect possible road regions in an image. A probabilistic hough transform based line segment detection combined with a clustering method is implemented to further extract the road. The proposed algorithm has been extensively tested on desert images obtained using an Unmanned Aerial Vehicle. Our results indicate that we are able to successfully and accurately detect roads in 96% of the images. We experimentally validated our algorithm on over a thousand aerial images obtained using our UAV. These images consist of straight and curved roads in various conditions with significant changes in lighting and intensity. We have also developed a road-tracking algorithm that searches a local rectangular area in successive images. Initial results are presented that shows the efficacy and the robustness of this algorithm. Using this road tracking algorithm we are able to further improve the road detection and achieve a 98% accuracy.     

一种有效的基于生活熵的移动用户分类算法

从海量移动用户通话记录中,根据用户的行为模式对用户进行分类挖掘.主要贡献包括:1)提出了生活熵的概念,用以刻画移动用户行为的规律性;2)提出基于生活熵的个人用户行为的分类算法;3)在大量真实移动数据集上进行了实验分析.利用本文提出的方法,可以有效的根据用户的行为特征对移动用户进行分类,在移动客户分析方面有较大的应用前景.     

CNF and DNF Considered Harmful for Computing Prime Implicants/Implicates

Several methods to compute the prime implicants and the prime implicates of a negation normal form (NNF) formula are developed and implemented. An algorithm PI is introduced that is an extension to negation normal form of an algorithm given by Jackson and Pais. A correctness proof of the PI algorithm is given. The PI algorithm alone is sufficient in a computational sense. However, it can be combined with path dissolution, and it is shown empirically that this is often an advantage. None of these variations rely on conjunctive normal form or on disjunctive normal form. A class of formulas is described for which reliance on CNF or on DNF results in an exponential increase in the time required to compute prime implicants/implicates. The possibility of avoiding this problem with efficient structure preserving clause form translations is examined briefly and appears unfavorable.     

A surface-scanning algorithm for displaying generalized cylinders

Generalized cylinders are objects defined by sweeping an arbitrary 2D closed contour along an arbitrary 3D trajectory while simultaneously scaling the contour in two perpendicular directions. A display algorithm for generalized cylinders is presented that is based on generating successive points on contours positioned at successive points on the trajectory. This surface-scanning algorithm requires that the contours as well as the points on a contour are taken close enough to guarantee that no gaps occur in the projected surface of the generalized cylinder. On the other hand, for the sake of efficiency, care has to be taken to restrict the number of super-fluous points. The paper describes solutions for these problems and shows that a surface-scanning algorithm is an elegant and efficient display algorithm for parametrically defined generalized cylinders.     

Structural inverse analysis by hybrid simplex artificial bee colony algorithms

A hybrid simplex artificial bee colony algorithm (HSABCA) which combines Nelder–Mead simplex method with artificial bee colony algorithm (ABCA) is proposed for inverse analysis problems. The proposed algorithm is applied to parameter identification of concrete dam-foundation systems. To verify the performance of HSABCA, it is compared with the basic ABCA and a real coded genetic algorithm (RCGA) on two examples: a gravity dam and an arc dam. Results show that the proposed algorithm is an efficient tool for inverse analysis and it performs much better than ABCA and RCGA on such problems.     

基于最大熵选取示例的增量决策树归纳

设A是一训练集,B是A的一个子集,B是选择A中部分有代表性的示例而生成的。得到了这样一个结论,即对于适当选取的B,由B训练出的决策树其泛化精度优于由A训练出的决策树的泛化精度。进一步,设计实现了一种如何从A中挑选有代表性的示例来生成B的算法,并从数据分布和信息熵理论角度分析了该算法的设计原理。     

公共交货期窗口下提前/拖期问题的多机调度算法

提出了求公共交货期窗口下提前／拖期都有惩罚的单机零件排序问题最优解的新算法,建立了相应多机零件排序问题的数学模型。在证明关于单机问题最优排序和最优公共交货期性质的若干定理的基础上,给出了求解多机问题的一个启发式算法。数值例子表明,该算法有较为理想的优化效果和工程实用价值。     

序信息系统中属性约简的启发式算法

基于序信息系统的知识粗糙熵,在系统中引入属性重要性的概念,利用该测度能度量序信息系统中属性集的不确定性,基于此,提出序信息系统中基于知识粗糙熵的启发式约简算法。通过实例对该方法的有效性进行检验,结果显示该算法可以作为一种有效的数据挖掘工具,为序信息系统的知识发现提供理论基础。     

Computing the Hough transform on a scan line array processor [imageprocessing]

A parallel algorithm for a line-finding Hough transform that runs on a linearly connected, SIMD (single-instruction, multiple-data-stream) vector of processors is described. The authors show that a high-precision transform, usually considered to be an expensive global operation, can be performed efficiently, in two to three times real time, with only local, communication on a long vector. The algorithm also illustrates a decomposition principle that has wide application in algorithm design for large linear arrays. A review of straight-line Hough transform implementations is also presented     

改进禁忌搜索算法的贴片机贴装过程优化

以多贴装头拱架式贴片机为研究对象,利用带块变异算子的改进禁忌算法实现实贴片机贴装过程的优化。在基本禁忌算法的基础上,利用块变异因子扩大元器件贴装顺序优化的搜索空间,并在禁忌搜索过程中利用局部迭代搜索实现喂料器的分配优化。为验证算法有效性,以10块实际生产的PCB为实例进行了测试。实验证明,提出的算法能获得更好的贴片机贴装优化解。