PMC模型下的一个贪婪诊断算法

提出了一种PMC模型下基于矩阵运算的贪婪诊断算法——MGFD算法。算法结合作者曾经提出的"绝对故障基"思想,首先剔除绝对故障基,得到一个维度减小的矩阵,之后根据该矩阵求得集团。在文献[10]提出的四个贪婪诊断算法的基础上,提出集团的内贪婪因子、外贪婪因子、综合贪婪因子等概念,设计了新的贪婪准则。论证了MGFD算法的正确性,并对算法进行了实验仿真。实验结果表明,MGFD算法相比文献[10]提出的贪婪诊断算法,具有较高的诊断正确率。     

一种主动视觉插轴入孔方法

本文提出了一个利用主动视觉实现空间任意斜面插轴入孔的方法，其相关算法包括主动视觉空间圆定位算法、主动视觉空间直线定位算法以及通过一个特征点估计相机姿态参数算法。通过建立以注视点为中心的相对坐标系，对零件之间的相对关系进行量测，其量测精度对于系统中诸如相机的绝对定位误差、机器人的绝对定位误差不敏感。用实际机器人系统进行实验的结果证明了该方法的有效性。该方法的思想可以扩展到其他形式的装配作业。     

蕴涵项的扩展算法

本文提出了一个把逻辑函数的积项扩展为本源蕴涵项的算法。用此算法得到的本源蕴涵项集合通过去冗过程产生的最后结果最接近绝对最小化的解。     

关于实质本源蕴涵项的识别问题

本文揭示ＥＳＰＲＥＳＳＯ算法和Ｍｕｒｏｇａ等提出的求绝对最小算法中识别实质本源蕴涵项的方法具有近似的复杂度。文中还给出了一个在产生本源蕴涵项过程中识别实质本源项的算法。     

一种新的机器人机构距离误差模型及补偿算法

在标定机器人绝对位置精度和实施误差综合补偿过程中,必然涉及到测量系统坐标系与机器人基础坐标系间的变换.由于这一变换很难精确测定.从而给机器人绝对位置精度标定与误差补偿带来了难以克服的困难.本文首次提出了一种新的机器人机构距离误差计算模型及补偿算法,论证了距离误差同样可以作为机器人绝对位置精度的一种度量.利用该模型和算法对机器人进行误差分析和实施误差综合补偿,可避开上述测量系统与机器人系统间的坐标变换,从而简化了机器人绝对位置精度的标定过程,为提高机器人的绝对位置精度开辟了一个新的简便的途径.     

设计Robust控制器的一个新准则和新算法

本文讨论具有最优输出调节品质的Robust控制器,利用绝对能观子系统的概念研究干扰 对闭环系统输出的影响.在一定条件下,从原系统中可分离出一个绝对能观子系统,这样使 输出调节的最优化计算得到简化. 本文给出了完成上述任务的一个算法.     

一种用于大数据的改进的ItemBased推荐算法

为了改善传统ItemBased推荐算法在大数据环境下的数据稀疏性问题和可扩展性问题,论文提出了一种基于Hadoop平台的ItemBased推荐算法.通过Pearson相关系数公式获取数据项之间的相关度,并根据数据集中的数据稀疏程度赋予一定的权值.在此基础上,将该算法在Hadoop平台上分布式并行化,在保证算法的平均绝对...     

抗冲击噪声的核对数最小绝对差算法

提出了一种鲁棒核自适应滤波算法,其结合了核空间和最小对数绝对差(LLAD)算法,使用对数代价函数来解决冲击噪声对算法收敛的影响,从而提高算法的抗干扰性能。核对数最小绝对差(KLLAD)算法实现了类似核最小均方误差(KLMS)算法的收敛性能,而且KLLAD算法具有很强的抗干扰能力,在非线性系统辨识中的鲁棒性和收敛方面具有很好的表现。     

大学生贫困资助评定的多粒度粗糙集研究

近年来,为保证家庭经济困难学生顺利完成学业,中央和地方各级政府制定了各种各样的政策,其中包括了大学贫困生资助这项政策。但同时也面临一个问题,就是如何判断学生是否贫困生。由于影响资助评定的因素有很多,导致资助评定存在不公平性。为了帮助各大高校更好地做好贫困生资助工作,设计了大学生贫困资助评定标准调查问卷,向某校大一至大四学生分发调查问卷收集数据,利用粗糙集理论改进的基于悲观多粒度约简算法、乐观多粒度约简算法以及双层绝对粒度约简算法,挖掘出影响贫困生评定标准的关键因素,并通过实验验证了结果的正确性。研究成果使得贫困生评定标准更加公正,让贫困生能在国家的资助下更好地完成学业,为以后的人生打好基石。     

MODIS数据地表温度反演劈窗算法比较

针对MODIS数据,分析比较了QIN和Wan-Dozier两种劈窗算法地表温度(LST)反演精度和误差分布。首先利用辐射传输模型MODTRAN4.0,结合TIGR大气廓线数据,评价两种算法绝对精度,然后基于误差传递理论分析评价二者的总精度,最后对两种算法的LST反演结果进行比较。研究表明针对所有廓线数据,两种算法绝对精度相差不大,但Wan-Dozier算法绝对精度受地表温度和水汽含量变化的影响程度要大于QIN算法;两种算法总精度相差不大,且主要误差源均为算法绝对精度和地表比辐射率精度,QIN算法反演结果对地表比辐射率的敏感性要略高于Wan-Dozier算法;两种算法得到研究区LST分布情况基本一致,均可表现空间LST分布差异,其中水体和裸土的LST反演结果差异较大,城镇和植被平均温度差异在0.5 K以内。     

逻辑函数求补算法及其改进

逻辑函数求补算法存在的主要问题是时间开销大及需要的存储空间过大。该文在对递归裂变求补算法和基于最小项求补算法进行分析研究的基础上,提出了积项输入、邻项合并、积项输出的无冗余覆盖的逻辑函数求补算法。该求补算法的时间、空间的需求将大大缩小。     

支持大规模变量集的最小覆盖迭代搜索算法

两级逻辑综合中的多输出逻辑电路最小覆盖的求解是一个NP难解问题,在输出变量集合和质蕴含项集合规模较大的情况下,会出现空间需求过大、处理时间太长等问题,影响多输出最小覆盖求解的可行性．在精选法的基础上,提出一种多输出最小覆盖迭代求解算法．将一次性求解最小覆盖的模式转换为多次迭代逼近最优解的过程,使得在有限的时间和空间范围内获得尽可能优化的最小覆盖结果．同时,对影响算法复杂度的单输出到多输出函数的阵列合并、极值的选择这2个主要环节进行了改进,大幅度降低了多输出最小覆盖求解算法的时间和空间复杂度．     

基于量子遗传算法的高效匹配搜索策略

在大规模源图像上进行图像匹配时,最佳匹配点的搜索策略是匹配算法时间性能的决定因素,设计高效匹配搜索策略是提高算法性能的关键。为了减少搜索时间和提高匹配实时性,本文基于匹配源图像划分和量子遗传算法基本原理,提出了面向大规模源图像匹配的目标淘汰搜索策略TESS。TESS将基于整幅源图像的全空间随机搜索的过程变成基于各个子图像的子空间并行搜索和逐步淘汰的过程,实现了匹配区域粗定位与匹配点精搜索的有效结合,从而大大缩短了最佳匹配点的搜索时间。实验结果表明,TESS搜索策略带来了匹配速度的极大提高,且时间加速比随匹配源图像规模的增大而增大。     

Two-machine flowshop scheduling with intermediate transportation under job physical space consideration

In this paper, we study a coordinated production–transportation scheduling problem in a two-machine flowshop environment where a single transporter may carry several jobs simultaneously as a batch between the machines. Each job has its own physical-space requirement while being loaded into the transporter. The goal is to minimize the makespan. For the jobs with the same size of physical space during transportation, we present a heuristic algorithm with an absolute worst-case ratio of 2 and a polynomial-time optimal algorithm for a special case with given job sequence. For the jobs having different size of physical storage space, a heuristic algorithm is constructed with an absolute worst-case ratio of 7/3 and asymptotic worst-case ratio of 20/9. Computational experiments demonstrate that the two heuristic algorithms developed are capable of generating near-optimal solutions quickly.     

A space-efficient algorithm for local similarities

Existing dynamic-programming algorithms for identifying similar regions of two sequences require time and space proportional to the product of the sequence lengths. Often this space requirement is more limiting than the time requirement. We describe a dynamic-programming local-similarity algorithm that needs only space proportional to the sum of the sequence lengths. The method can also find repeats within a single long sequence. To illustrate the algorithm's potential, we discuss comparison of a 73,360 nucleotide sequence containing the human beta-like globin gene cluster and a corresponding 44,594 nucleotide sequence for rabbit, a problem well beyond the capabilities of other dynamic-programming software.     

A robust self-tuning scheme for PI- and PD-type fuzzy controllers

Proposes a simple but robust model independent self-tuning scheme for fuzzy logic controllers (FLCs). Here, the output scaling factor (SF) is adjusted online by fuzzy rules according to the current trend of the controlled process. The rule-base for tuning the output SF is defined on error (e) and change of error (Δe) of the controlled variable using the most natural and unbiased membership functions (MFs). The proposed self-tuning technique is applied to both PI- and PD-type FLCs to conduct simulation analysis for a wide range of different linear and nonlinear second-order processes including a marginally stable system where even the well known Ziegler-Nichols tuned conventional PI or PID controllers fail to provide an acceptable performance due to excessively large overshoot. Performances of the proposed self-tuning FLCs are compared with those of their corresponding conventional FLCs in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error and integral-of-time-multiplied absolute error, in addition to the responses due to step set-point change and load disturbance and, in each case, the proposed scheme shows a remarkably improved performance over its conventional counterpart     

Accelerating ARTS

A major fraction of ray-tracing computation time is spent on ray-object intersection calculation. To reduce this calculation cost, one method, ARTS, subdivides the 3-D object space into voxels and uses a 3-D line-drawing routine to simulate ray propagation in the subdivided space to select objects for intersection testing. Finer space subdivision gives better object selection resolution and fewer ray-object tests. However, as the subdivision increases, the improvement is offset by a linear degradation of the line-drawing-routine efficiency and a cubic growth of the memory requirement. We solve these time and memory scalability problems in ARTS using an adaptive 3-D line-drawing algorithm, which traverses space with multiple stepsizes, and a hybrid database that employs both the octree and the 3-D array data structures. The space traversal cost in our solution grows logarithmically with the subdivision increase, and the memory requirement grows only linearly.     

Another Look at LTL Model Checking

We show how LTL model checking can be reduced to CTL model checking with fairness constraints. Using this reduction, we also describe how to construct a symbolic LTL model checker that appears to be quite efficient in practice. In particular, we show how the SMV model checking system developed by McMillan [16] can be extended to permit LTL specifications. The results that we have obtained are quite surprising. For the specifications which can be expressed in both CTL and LTL, the LTL model checker required at most twice as much time and space as the CTL model checker. We also succeeded in verifying non-trivial LTL specifications. The amount of time and space that is required is quite reasonable. Based on the examples that we considered, it appears that efficient LTL model checking is possible when the specifications are not excessively complicated.     

Pipelined processors and worst case execution times

The calculation of worst case execution time (WCET) is a fundamental requirement of almost all scheduling approaches for hard real-time systems. Due to their unpredictability, hardware enhancements such as cache and pipelining are often ignored in attempts to find WCET of programs. This results in estimations that are excessively pessimistic. In this article a simple instruction pipeline is modeled so that more accurate estimations are obtained. The model presented can be used with any schedulability analysis that allows sections of nonpreemptable code to be included. Our results indicate the WCET overestimates at basic block level can be reduced from over 20% to less than 2%, and that the overestimates for typical structured real-time programs can be reduced by 17%–40%.     

ERFC: An Enhanced Recursive Flow Classification Algorithm

Packet classification on multi-fields is a fundamental mechanism in network equipments, and various classification solutions have been proposed. Because of inherent difficulties, many of these solutions scale poorly in either time or space as rule sets grow in size. Recursive Flow Classification (RFC) is an algorithm with a very high classifying speed. However, its preprocessing complexity and memory requirement are rather high. In this paper, we propose an enhanced RFC (ERFC) algorithm, in which a hash-based aggregated bit vector scheme is exploited to speed up its preprocessing procedure. A compressed and cacheable data structure is also introduced to decrease total memory requirement and improve its searching performance. Evaluation results show that ERFC provides a great improvement over RFC in both space requirement and preprocessing time. The search time complexity of ERFC is equivalent to that of RFC in the worst case; and its average classifying speed is improved by about 100%.