Is the Polar Relative Monodromy of Finite Order？ An Example

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Vague集综合评价中单值指标规范化研究

不同指标值的规范化是使用Vague集综合评价的第一步.针对现有算法的不足,根据Vague集理论,提出了效益型、成本型、固定型、区间型、偏离型、偏离区间型等六种类型单值指标Vague集规范化新算法,通过实例验证了新规范化算法的有效性,合理性和高分辨性.     

社交网络环境下基于单值中智信息的大规模群决策方法

考虑到单值中智集具有全面且准确描述不确定信息的优势,文章提出了社交网络环境下基于单值中智信息的大规模群决策方法.首先,结合Louvain算法对社交网络进行分区,并确定分区团体中各决策者权重以及分区团体在整个社交网络中的权重.其次,提出改进的单值中智加权平均算子与改进的单值中智有序加权平均算子,并探讨算子的合理性以及相关性质.结合所提算子,对分区团体中各决策者的偏好信息以及整个网络中决策者的偏好信息进行集结.再次,采用单值中智距离测度检测分区团体中决策者的一致性水平,并利用改进的单值中智加权平均算子与单值中智数比较方法对候选方案进行排序.最后,结合中国某海外矿产投资项目选择案例验证所提方法的可行性与有效性,并通过灵敏度分析与比较分析证明所提方法的优越性.     

Fuzzy度量空间中的单值映射的Caristi型不动点定理

本文采用Ｋａｌａｖａ和Ｓｅｉｋｋａｌａ的模糊度量空间定义，利用文（７）中建立的亚度量簇生成空间理论，研究了Ｆｕｚｚｙ度量空间中的单值映射的Ｃａｒｉｓｔｉ型不动点定理以及它在Ｍｅｎｇｅｒ概率度量空间中的应用。     

定积分应用中一个值得注意的问题

一些通用教材在介绍由参数方程表示的封闭曲线围成的区域面积计算时，依据的公式往往是只适用于广义曲边梯形，并且y=f(x)是x的单值函数的情形，从而容易出现错误，在用极坐标方程计算旋转体体积时也有类似的情形。     

基于单值中智集Choquet积分算子的群决策方法

单值中智集不仅能描述现实决策系统中不完整信息而且能描述不确定性和不一致信息,已有关于单值中智集的决策方法只能用来解决属性间相互独立的多属性决策问题.考虑到Choquet积分算子的特点,将Choquet积分算子应用到单值中智集中,用以解决属性间有关联关系的多属性群决策问题.首先应用单值中智集余弦相似度比较方法,提出了单值中智集Choquet积分算子,研究了其性质.然后建立了基于单值中智集Choquet积分算子的多属性群决策方法.最后通过实例分析说明了算法的可行性和有效性.     

Riccati方程的代数曲线解及其单值群

本文给出了Riccati方程ω’＝ω’＋f（z）有形如的代数曲线解的充要条件及其求解方法，证明了有解时相应的Fuchs方程的单值群是可解的，并讨论了数学物理中的几个著名方程．     

模糊值Choquet积分(Ⅱ)--函数关于模糊值模糊测度的Choquet积分

研究一种取值于模糊数集的Choquet积分，该积分的被积函数是单值函数，所用的测度是模糊值模糊测度。给出其定义、性质和收敛定理。     

tt*几何的等单值τ函数

在本文中, 作者定义了Landau-Ginzburg B{-}模型中的tt^*几何结构对应的等单值τ函数. 基于Getzler, Dubrovin-Zhang 在亏格1的Gromov-Witten理论的部分工作,作者将所定义的τ函数和物理上给出的亏格1的Landau-Ginzburg B{-}模型的生成函数联系起来.     

Depth notions for orthogonal regression

Global depth, tangent depth and simplicial depths for classical and orthogonal regression are compared in examples, and properties that are useful for calculations are derived. The robustness of the maximum simplicial depth estimates is shown in examples. Algorithms for the calculation of depths for orthogonal regression are proposed, and tests for multiple regression are transferred to orthogonal regression. These tests are distribution free in the case of bivariate observations. For a particular test problem, the powers of tests that are based on simplicial depth and tangent depth are compared by simulations.     

Numerical methods for Hamilton Jacobi functional differential equations

Initial and initial boundary value problems for first order partial functional differential equations are considered. Explicit difference schemes of the Euler type and implicit difference methods are investigated. The following theoretical aspects of the methods are presented. Sufficient conditions for the convergence of approximate solutions are given and comparisons of the methods are presented. It is proved that assumptions on the regularity of given functions are the same for both the methods. It is shown that conditions on the mesh for explicit difference schemes are more restrictive than suitable assumptions for implicit methods. There are implicit difference schemes which are convergent and corresponding explicit difference methods are not convergent. Error estimates for both the methods are construted.     

Mixtures of Global and Local Edgeworth Expansions and Their Applications

Edgeworth expansions which are local in one coordinate and global in the rest of the coordinates are obtained for sums of independent but not identically distributed random vectors. Expansions for conditional probabilities are deduced from these. Both lattice and continuous conditioning variables are considered. The results are then applied to derive Edgeworth expansions for bootstrap distributions, for Bayesian bootstrap distribution, and for the distributions of statistics based on samples from finite populations. This results in a unified theory of Edgeworth expansions for resampling procedures. The Bayesian bootstrap is shown to be second order correct for smooth positive “priors,” whenever the third cumulant of the “prior” is equal to the third power of its standard deviation. Similar results are established for weighted bootstrap when the weights are constructed from random variables with a lattice distribution.     

Invertibility and Spectrum of Hille–Tamarkin Matrices

Hille–Tamarkin matrices are investigated.Invertibility conditions and estimates for the norm of the inverse matrices are established. In addition, bounds for the spectrum are suggested. In particular, new estimates for the spectral radius are derived.     

On contraction of nonlinear difference equations with time‐varying delays

General nonlinear difference equations with time‐varying delays are considered. Explicit criteria for contraction of such equations are presented. Then some simple sufficient conditions for global exponential stability of equilibria and for stability of invariant sets are derived. Furthermore, explicit criteria for existence, uniqueness and global exponential stability of periodic solutions are derived. Finally, the obtained results are applied to time‐varying discrete‐time neural networks with delay.     

B-vex Fuzzy Mappings and Its Application to Fuzzy Optimization Problems

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SOR-like Methods for Augmented Systems

Several SOR-like methods are proposed for solving augmented systems. These have many different applications in scientific computing, for example, constrained optimization and the finite element method for solving the Stokes equation. The convergence and the choice of optimal parameter for these algorithms are studied. The convergence and divergence regions for some algorithms are given, and the new algorithms are applied to solve the Stokes equations as well.     

Determinant formulas with applications to designing when the observations are correlated

In the general linear model consider the designing problem for the Gauß-Markov estimator or for the least squares estimator when the observations are correlated. Determinant formulas are proved being useful for theD-criterion. They allow, for example, a (nearly) elementary proof and a generalization of recent results for an important linear model with multiple response. In the second part of the paper the determinant formulas are used for deriving lower bounds for the efficiency of a design. These bounds are applied in examples for tridiagonal covariance matrices. For these examples maximin designs are determined.Parts of the paper are based on a part of the author's Habilitationsschrift Bischoff (1993a).     

Manufacturing flow line systems: a review of models and analytical results

The most important models and results of the manufacturing flow line literature are described. These include the major classes of models (asynchronous, synchronous, and continuous); the major features (blocking, processing times, failures and repairs); the major properties (conservation of flow, flow rate-idle time, reversibility, and others); and the relationships among different models. Exact and approximate methods for obtaining quantitative measures of performance are also reviewed. The exact methods are appropriate for small systems. The approximate methods, which are the only means available for large systems, are generally based on decomposition, and make use of the exact methods for small systems. Extensions are briefly discussed. Directions for future research are suggested.     

Convergence of classes of subpramarts and games which become better with time

In this paper local convergence theorems for subpramarts and GBTs (games which become better with time) are presented. These results are also new for Martingales. Global convergence theorems for subpramarts and GBTs are also proved. These theorems are related to the theory of optimal stopping.