基于Vague集相似度量的多准则模糊决策方法

在分析已有关于Vague值（集）相似度量方法存在不足的基础上，综合考虑Vague值区间端点间的距离、核距离以及未知部分对支持度和反对度的影响等主要因素，提出了一种新的Vague值（集）相似度量方法，并对其性质进行讨论. 通过与现有方法的比较，表明该方法具有很强的相似度区分能力. 最后将所提出的Vague值（集）相似度量用于多准则模糊决策中，通过最优化方法选取每个准则的最优权重，根据候选方案与理想方案在相应准则下相似度加权和的大小得出最佳方案. 通过实例分析，表明了这种方法的有效性和可行性.     

基于空间点特征和改进Hausdorff距离的图像配准方法

在基于特征的图像配准中,针对基于边缘的Hausdorff距离计算效率低的问题,提出用能表示图像空间结构的特征点来进行Hausdorff距离计算的方法。该方法是通过检测图像中的特征点来减少匹配点集中点的数量,实验证明了该方法的有效性,以及在计算和匹配时间上要优于基于边缘特征的Hausdorff距离计算方法。针对稀疏特征点集的特点,提出了改进Hausdorff距离,该距离通过改进部分Hausdorff距离使其更加适用于稀疏点集的距离计算,实验表明该距离在抗噪等方面优于其他Hausdorff距离。     

多粒度犹豫模糊语言信息下的群推荐方法

针对群推荐系统的偏好信息来自不同的网络平台,被推荐项目具有多粒度性、犹豫模糊性和多属性等问题.本文首先定义了多粒度犹豫模糊语言术语集的概念,定义了多粒度犹豫模糊语言术语集的广义距离公式、广义豪斯多夫距离公式和广义混合距离公式;其次,考虑被推荐项目属性的权值问题,定义了相应的广义加权距离公式距离、广义加权豪斯多夫距离公式和广义混合加权距离公式等.研究了这些公式的性质,讨论了公式之间的关系;最后,将这些距离公式结合满意度公式用于群体推荐问题,并进一步分析了公式的参数对满意度及电影排序的影响情况.     

特征匹配驱动的IVIFSs相似性测度模型研究

直觉模糊集(intuitionistic fuzzy sets,IFSs)的隶属关系表征并不完全适用于区间直觉模糊集(interval-valued intuitionistic fuzzy sets, IVIFSs),故其相似性测度模型与特征条件难以实现完全匹配。首先,运用记分函数和精确函数来刻画IVIFSs的特征条件,分析了现有IVIFSs相似性测度模型与特征条件匹配的冲突性;其次,基于其几何距离和重心设计了一种新的IVIFSs相似性测度模型;最后,通过理论证明和实证研究分析了该模型的优越性和应用价值。     

基于曲线相似的在线签名认证方法

提出一种新的曲线相似计算模型,用于在线签名身份认证。将在线签名轨迹数据看做平面曲线,从曲线相似性定义、相似变换及相似距离给出了曲线相似计算模型框架。依照参考签名曲线有效点数,对比较签名曲线进行重采样;签名曲线相似度量过程采用分段匹配方法,在每段比较曲线待匹配区间内,利用遗传算法搜索与参考曲线对应段的最优匹配,获得分段的相似距离,以此计算分段相似得分;将各段相似得分的平均值作为两条曲线的相似度量。选用SVC2004 Task1和SUSig Blind数据集对算法进行测试,等误率分别为10.92%和2.89%。     

Test on Stochastic Block Model: Local Smoothing and Extreme Value Theory

In this paper, to obtain a consistent estimator of the number of communities, the authors present a new sequential testing procedure, based on the locally smoothed adjacency matrix and the extreme value theory. Under the null hypothesis, the test statistic converges to the type I extreme value distribution, and otherwise, it explodes fast and the divergence rate could even reach n in the strong signal case where n is the size of the network, guaranteeing high detection power. This method is simple to use and serves as an alternative approach to the novel one in Lei (2016) using random matrix theory. To detect the change of the community structure, the authors also propose a two-sample test for the stochastic block model with two observed adjacency matrices. Simulation studies justify the theory. The authors apply the proposed method to the political blog data set and find reasonable group structures.

     

Science as Systemic Intervention: Some Implications of Systems Thinking and Complexity for the Philosophy of Science

This paper sidesteps the usual starting points for debate about complexity and the philosophy of science, which tend to assume that science is primarily about observation. Instead, the starting point is intervention, defined as purposeful action by an agent to create change. While some authors suggest that intervention and observation are opposites, it is argued here that observation (as undertaken in science) should be viewed as just one type of intervention. We should therefore welcome scientific techniques of observation into a pluralistic set of intervention methods, alongside methods for exploring values, reflecting on subjective understandings, planning future activities, etc. However, there is a need to explicitly counter a possible pernicious interpretation of this argument: intervention could (erroneously) be viewed as flawlessly preplanned change based on accurate predictions of the consequences of action. This is the mechanistic worldview that systems thinking and complexity science seek to challenge. Therefore, having redefined scientific observation as intervention, the paper revisits insights from systems thinking and complexity to propose a methodology of systemic intervention. Some brief reflections are then provided on the wider social implications of this methodology.     

区间主成分分析方法的比较

简述了区间数据主成分分析(PCA)的两种主要方法--顶点法(V-PCA)和中点法(C-PCA),并对其进行了合理化改进.研究表明,两种方法的协方差矩阵有极大的相似性.在研究区间数距离的基础上,定义了一种基于Hausdorff距离的评价模型方法优劣的效度指标,并通过模拟的方法,对这两种方法进行了比较研究.结果表明:两种方法具有较强的相似性;随着变量数和样本数的增加,两种方法的效度均有所下降;在同样的样本数条件下,中点法适合变量数较大的情形,而顶点法更适合于变量数较小的情形.最后,给出了区间PCA方法选择及效度测量的应用步骤和一个算例.     

基于Hausdorff度量模糊多指标群决策的TOPSIS方法

针对模糊多指标群决策中模糊数的比较与排序问题 ,定义了模糊数的 Hausdorff度量与乐观 -悲观效用函数 ,根据乐观 -悲观效用函数求出模糊多指标群决策问题的理想点和负理想点 ,进而由 Haus-dorff度量获得不同备选方案到理想点与负理想点的距离及其贴近度 ,从而在模糊多指标群决策中托展了理想点逼近方法 .最后 ,就带三角形模糊数与梯形模糊数的多指标群决策问题分别进行了深入的讨论 .     

聚类分析算法在交通控制中的应用

聚类分析是根据物理或抽象对象间的相似程度对对象进行分类的一种方法，通过聚类分析使得同一类中的对象具有高的相似度，而与其他类中的对象则很不相同。PAM(Partitioning Around Medoids)算法是一种基于距离的分离式聚类方法，具有良好的抗噪声、抗偏离点的能力。本文将PAM算法应用于交通控制的时段划分中，通过验证分析．结果表明取得了良好的分类效果。     

景象匹配辅助导航中多级实时匹配算法研究

由于选用部分Hausdorff距离进行图像匹配时不能满足较大尺寸图像匹配实时性要求,利用了多级分层匹配技术加速图像匹配,提出了多级实时图像匹配算法,该算法以部分Hausdorff距离为图像匹配相似性度量,结合小波变换多分辨率思想提取多尺度图像特征,实现了由粗到精多级分层实时匹配。图像匹配结果表明,光学卫星(IKONOS)图像和合成孔径雷达(SAR)图像二种情况下图像匹配结果准确,比仅采用基于部分Hausdorff距离图像匹配而言,采用三级图像匹配可大大缩短匹配时间。该算法实施景象匹配能在5 s以内完成,满足景象匹配辅助导航系统匹配修正的准确性和实时性的要求。     

Vague 值与Vague 集上的贴近度

基于“投票模型”,给出一个一般的贴近度表达式,该表达式把Chen的公式、Hong和Kim的公式、李和徐的公式作为特例.基于这个一般表达式,定义了一些新的贴近度公式并讨论了这些公式具有的性质,为更好的应用这些公式奠定了必要的基础.     

The recursive solution of queue length for <Emphasis Type="Italic">Geo/G</Emphasis>/1 queue with <Emphasis Type="Italic">N</Emphasis>-policy

This paper considers a discrete-time queue with N-policy and LAS-DA(late arrival system with delayed access) discipline.By using renewal process theory and probability decomposition techniques,the authors derive the recursive expressions of the queue-length distributions at epochs n~-,n~+,and n.Furthermore,the authors obtain the stochastic decomposition of the queue length and the relations between the equilibrium distributions of the queue length at different epochs(n~-,n~+,n and departure epoch D_n).     

Construction and comparisons of simultaneous confidence intervals for the mean difference of multivariate normal distributions

<正> In this paper,Scheffé and Simplified Scheffé simultaneous confidence intervals are firstconstructed for mean difference of several multivariate normal distributions.Then the authors theoreticallyprove that when there are only two populations,Bonferroni bounds and Simplified Scheffébounds are the same and they are shorter than Scheffé bounds for p10.In the case for 3k10and 2p10,there exists n(p,k)such that Bonferroni method is better than Simplified Schefféprocedure for nn(p,k),otherwise Simplified Scheffé procedure is better.Finally,the authors findout that neither of Scheffé critical values nor Simplified Scheffé critical values are always larger thananother through numerical calculation.     

Distance-Based Regression Analysis for Measuring Associations

Distance-based regression model, as a nonparametric multivariate method, has been widely used to detect the association between variations in a distance or dissimilarity matrix for outcomes and predictor variables of interest in genetic association studies, genomic analyses, and many other research areas. Based on it, a pseudo-F statistic which partitions the variation in distance matrices is often constructed to achieve the aim. To the best of our knowledge, the statistical properties of the pseudo-F statistic has not yet been well established in the literature. To fill this gap, the authors study the asymptotic null distribution of the pseudo-F statistic and show that it is asymptotically equivalent to a mixture of chi-squared random variables. Given that the pseudo-F test statistic has unsatisfactory power when the correlations of the response variables are large, the authors propose a square-root F-type test statistic which replaces the similarity matrix with its square root. The asymptotic null distribution of the new test statistic and power of both tests are also investigated. Simulation studies are conducted to validate the asymptotic distributions of the tests and demonstrate that the proposed test has more robust power than the pseudo-F test. Both test statistics are exemplified with a gene expression dataset for a prostate cancer pathway.

     

航天器三维空间追逃问题研究

针对固定时间下的两航天器三维空间追逃问题,采用协同进化算法将复杂的双边最优规划问题简化成对追逃过程中纳什均衡点的搜索,进而得出追逃双方的最优对抗策略及解算方法。考虑在保证算法计算精度的前提下缩短计算时间,将对策模型进行简化处理,以航天器推力指向角为控制量对协同进化算法进行编码设计,利用B样条基函数对编码进行逼近拟合。两航天器均为连续小推力作用,以二者的末端相对距离作为支付函数,逃逸器希望支付最大,追踪器希望支付最小,并依此建立共享适应度函数。所提方法中对协同算子进行改进设计,提高算法空间搜索能力,并采用精英保留策略提高算法的收敛速度。仿真算例得到追逃双方的最优控制策略及相应的追逃轨迹,表明所提方法的能够解决此类航天器追逃问题。     

The conditional diagnosability of shuffle-cubes

<正> In the application of multiple-processor systems some processors or links in a system maynot function properly,thus the fault diagnosis is one of the most important issues in the analysisand maintenance of those systems.For the practical fault diagnosis systems,the probability that allneighboring processors of a processor are faulty simultaneously is very small.Thus,the conditionaldiagnosability,which is a new metric for evaluating such systems,assumes that every fault set doesnot contain all neighbors of any processor in the system.In this paper,the authors show that then-dimensional shuffle-cube has the conditional diagnosability of 4n-15 for n = 2 (mod 4) and n ≥ 10.     

Proper reparametrization for inherently improper unirational varieties

In this paper, a class of lattice supports in the lattice space Z ^m is found to be inherently improper because any rational parametrization from C ^m to C ⁿ defined on such a support is improper. The improper index for such a lattice support is defined to be the gcd of the normalized volumes of all the simplex sub-supports. The structure of an improper support S is analyzed and shrinking transformations are constructed to transform S to a proper one. For a generic rational parametrization RP defined on an improper support S, we prove that its improper index is the improper index of S and give a proper reparametrization algorithm for RP. Finally, properties for rational parametrizations defined on an improper support and with numerical coefficients are also considered.     

节域为负无穷区间和全体实数域的初等关联函数构造

关联函数是可拓集合的核心, 它的构造方法是可拓学的重要研究内容. 在定义点与负无穷区间和点与全体实数域之距的基础上, 构造了正域为有限区间和节域分别为负无穷区间和全体实数域的位值公式及相应的初等关联函数并得到若干性质, 使可拓学在定量化描述各领域矛盾问题时具有更宽的适用范围.     

基于三维模型的多传感车辆定位与识别研究

车辆的定位与识别是智能车研究的重要环节。针对二维算法及单传感的不足,提出了一种基于三维模型的多传感车辆定位与识别算法。定位系统中,通过将雷达的位置估计和图像的灰度信息进行融合来获得位移参数,并将改进的Hausdorff距离和模拟退火算法相结合得到旋转参数。在此基础上,识别系统计算每个模型与目标车辆的匹配值,根据其在采样时段内的平均值确定车辆类型。实验证明,该方法能有效地实现目标车辆的定位和识别。