大学生综合素质的评价方法与应用

简述了因子分析法,雷达图法和聚类分析法的理论知识.利用因子分析法,雷达图法和聚类分析法,对学生的成绩进行全面分析,得到学生综合素质的合理评价.结果表明,较以往常用的两种方法(平均积点分和综合测评总分),方法更具有科学性与合理性.     

模糊模式识别方法在学生综合素质评价中的应用

给出了一种基于模糊模式识别的学生综合素质评判方法 ,并且考虑了各因素不同的重要程度 ,对其他评价方法作了有益的补充 .     

管制员综合素质评价方法研究

管制员综合素质对管制系统安全运行有着重要的作用.为保证管制系统安全运行,提出了一种使用三元区间数基本理论的管制员综合素质评价方法,对管制员综合素质进行评价.根据少数服从多数原则,给出了一种计算群决策专家权重系数的新方法,考虑专家系数,给出了一种构造三元区间数的方法,通过排序函数确定最大三元区间数,通过指标对应三元区间数与最大区间数比值的模确定指标初始权重,并对指标权重公平化处理,得到指标最终权重,并在此基础上建立了管制员综合素质评价模型.算例结果表明,所提出的评价方法能够度管制员综合素质进行有效评价.     

一种可用于生产效率评价的灰靶评估算法

本文在分析和比较了DEA和灰靶评估两种方法之后，给出一种可用于生产效率评价的灰靶评估算法。该算法由于运用了DEA方法中的“生产效率”概念，弥补了灰靶评估算法不能对不同的被评价单元进行效率评价的不足，从而拓宽了灰靶评估算法的应用背景。文章最后给出实例分析。     

多层次指标投影与模糊综合评判结论的因果分析

数据包络分析方法与模糊综合评判方法是两个十分重要但又相互独立的评价方法，如果能够找到两种方法的关联关系，进而实现两种方法的优势互补将是一项值得探讨的工作。另外，模糊指标合成后，要想应用数据包络分析方法找到更微观指标的改进信息也非常困难。为解决这些问题，本文首先基于模糊综合评判的已有信息，构建多层次模糊评价结果的可能集，并提出多层次模糊投影的定义及相应的计算公式。在此基础上，给出了测度模糊事件存在不足的定量方法。最后，以中国14个旅游省区的游客满意度为例进行了实证分析。     

线性无量纲化方法在群体评价中的扩展及选取

无量纲化处理是开展综合评价的基础，目前线性无量纲化方法很少考虑群体评价的情况。本文针对常用的6种线性无量纲化方法直接应用到群体评价中不能保证各评价者评价信息横向大小顺序的问题，首先对问题进行界定，并对6种线性无量纲化方法进行了扩展；其次进一步分析了扩展后的线性无量纲化方法的性质，并针对群体评价问题引入“横向单调性”和“变量单一性”两个性质，为线性无量纲化方法的设计研究提供重要的参考；再次以无量纲化后的数据最大程度的保留原始信息为原则，针对不同的赋权方法，给出线性无量纲化方法选择的建议；最后，用一个算例检验了方法的有效性。     

我国普通高等教育人力资源发展水平的统计分析

本文综合运用主成分分析和因子分析两种综合评价方法 ,对我国各地区高等教育人力资源的发展水平进行排序和分类 ,为规划和发展各地区的高等教育事业提供了一定的科学依据。两种综合评价方法的综合运用克服了单一评价方法的片面性 ,评价结果较为全面、客观     

基于灰色聚类分析和TOPSIS的上市银行创新能力评价

增强创新能力是银行在利率市场化和金融脱媒时代下提高自身竞争力的重要方式.从银行经营能力和金融创新能力两方面出发,选取可体现银行特征的经营情况指标和广泛应用金融创新评价指标构建银行创新力评价指标体系.以30家上市银行为研究对象,基于2015-2019年数据,分别运用灰色聚类和熵权TOPSIS的方法对上市银行创新能力进行评价,紧接着对两种评价体系下上市银行的表现进行分析,并根据两种方法的评价结果提出了一种综合排名方法,形成了同时考虑两种方法的综合排名结果.     

基于DEA方法和粗糙集的政府效率评估模型

政府效率影响政府的执政能力。评价政府效率必须考虑投入和产出之间的关系。本文首先利用DEA方法建立投入一产出多指标模型评价政府工作的相对有效性，并对评价结果进行离散化处理；然后运用粗糙集方法对离散后的数据进行分析，得出每个待评对象的综合评分。两种方法的有机结合，使得建立的政府效率评价模型既能充分反映政府效率投入一产出的特点，又能有效避免人为因素对模型的影响，以得到更合理的评估结果。     

采用优化模型指标筛选的马田系统综合评价方法研究

传统的马田系统主要用于分类与诊断.将马田系统作为一种综合评价方法进行研究,分别研究了有基准空间和无基准空间两种情形下的马田系统综合评价方法及步骤.针对传统马田系统变量筛选存在的缺陷,构建多目标规划模型进行评价指标筛选,采用遗传算法求解模型.通过两个实际案例,将马田系统综合评价方法与一些常用的综合评价方法对比研究,结果表明,马田系统可以筛选评价指标和避免指标赋权问题,是一种实用且有效的综合评价方法.     

Expanding stability regions of explicit advective-diffusive finite difference methods by Jacobi preconditioning

Explicit time differencing methods for solving differential equations are advantageous in that they are easy to implement on a computer and are intrinsically very parallel. The disadvantage of explicit methods is the severe restrictions that are placed on stable time-step intervals. Stability bounds for explicit time differencing methods on advective–diffusive problems are generally determined by the diffusive part of the problem. These bounds are very small and implicit methods are used instead. The linear systems arising from these implicit methods are generally solved by iterative methods. In this article we develop a methodology for increasing the stability bounds of standard explicit finite differencing methods by combining explicit methods, implicit methods, and iterative methods in a novel way to generate new time-difference schemes, called preconditioned time-difference methods. A Jacobi preconditioned time differencing method is defined and analyzed for both diffusion and advection–diffusion equations. Several computational examples of both linear and nonlinear advective-diffusive problems are solved to demonstrate the accuracy and improved stability limits. © 1995 John Wiley & Sons, Inc.     

几类改进的新的两步六阶Chebyshev-Halley方法

利用权函数法,给出非线性方程求根的Chebyshev-Halley方法的几类改进方法,证明方法六阶收敛到单根.Chebyshev-Halley方法的效率指数为1.442,改进后的两步方法的效率指数为1.565.最后给出数值试验,且与牛顿法,Chebyshev-Halley 方法及其它已知的方程求根方法做了比较.结果表明方法具有一定的优越性.     

Direct prediction methods in Hilbert space with applications to control problems

In this paper, the convergence of variable-metric methods without line searches (direct prediction methods) applied to quadratic functionals on a Hilbert space is established. The methods are then applied to certain control problems with both free endpoints and fixed endpoints. Computational results are reported and compared with earlier results. The methods discussed here are found to compare favorably with earlier methods involving line searches and with other direct prediction quasi-Newton methods.     

New Multivalue Methods for Differential Algebraic Equations

Multivalue methods are slightly different from the general linear methods John Butcher proposed over 30 years ago. Multivalue methods capable of solving differential algebraic equations have not been developed. In this paper, we have constructed three new multivalue methods for solving DAEs of index 1, 2 or 3, which include multistep methods and multistage methods as special cases. The concept of stiff accuracy will be introduced and convergence results will be given based on the stage order of the methods. These new methods have the diagonal implicit property and thus are cheap to implement and will have order 2 or more for both the differential and algebraic components. We have implemented these methods with fixed step size and they are shown to be very successful on a variety of problems. Some numerical experiments with these methods are presented.     

The composite Milstein methods for the numerical solution of Stratonovich stochastic differential equations

In this paper, we present two composite Milstein methods for the strong solution of Stratonovich stochastic differential equations driven by d-dimensional Wiener processes. The composite Milstein methods are a combination of semi-implicit and implicit Milstein methods. The criterion for choosing either the implicit or the semi-implicit method at each step of the numerical solution is given. The stability and convergence properties of the proposed methods are analyzed for the linear test equation. It is shown that the proposed methods converge to the exact solution in Stratonovich sense. In addition, the stability properties of our methods are found to be superior to those of the Milstein and the composite Euler methods. The convergence properties for the nonlinear case are shown numerically to be the same as the linear case. Hence, the proposed methods are a good candidate for the solution of stiff SDEs.     

New splitting methods for two-dimensional evolutionary equations

New second- and third-order splitting methods are proposed for evolutionary-type partial differential equations in a two-dimensional space. These methods are derived on the basis of diagonally implicit methods applied to the numerical analysis of stiff ordinary differential equations. The splitting methods are found to be absolutely unconditionally stable. Test calculations are presented.     

Delay-dependent stability analysis of multistep methods for delay differential equations

This paper deals with the delay-dependent stability of numerical methods for delay differential equations. First, a stability criterion of Runge-Kutta methods is extended to the case of general linear methods. Then, linear multistep methods are considered and a class of r（0）-stable methods are found. Later, some examples of r（0）-stable multistep multistage methods are given. Finally, numerical experiments are presented to confirm the theoretical results.     

IMPLICIT-EXPLICIT RUNGE-KUTTA-ROSENBROCK METHODS WITH ERROR ANALYSIS FOR NONLINEAR STIFF DIFFERENTIAL EQUATIONS

Implicit-explicit Runge-Kutta-Rosenbrock methods are proposed to solve nonlinear stiff ordinary differential equations by combining linearly implicit Rosenbrock methods with ex-plicit Runge-Kutta methods.First,the general order conditions up to order 3 are obtained.Then,for the nonlinear stiff initial-value problems satisfying the one-sided Lipschitz condi-tion and a class of singularly perturbed initial-value problems,the corresponding errors of the implicit-explicit methods are analysed.At last,some numerical examples are given to verify the validity of the obtained theoretical results and the effectiveness of the methods.     

Fourth-Order Splitting Methods for Time-Dependant Differential Equations

This study was suggested by previous work on the simulation of evolution equations with scale-dependent processes,e.g.,wave-propagation or heat-transfer,that are modeled by wave equations or heat equations.Here,we study both parabolic and hyperbolic equations.We focus on ADI (alternating direction implicit) methods and LOD (locally one-dimensional) methods,which are standard splitting methods of lower order,e.g.second-order.Our aim is to develop higher-order ADI methods,which are performed by Richardson extrapolation,Crank-Nicolson methods and higher-order LOD methods,based on locally higher-order methods.We discuss the new theoretical results of the stability and consistency of the ADI methods.The main idea is to apply a higher- order time discretization and combine it with the ADI methods.We also discuss the dis- cretization and splitting methods for first-order and second-order evolution equations. The stability analysis is given for the ADI method for first-order time derivatives and for the LOD (locally one-dimensional) methods for second-order time derivatives.The higher-order methods are unconditionally stable.Some numerical experiments verify our results.     

Empirical likelihood confidence intervals for hazard and density functions under right censorship

In this paper, we use smoothed empirical likelihood methods to construct confidence intervals for hazard and density functions under right censorship. Some empirical log-likelihood ratios for the hazard and density functions are obtained and their asymptotic limits are derived. Approximate confidence intervals based on these methods are constructed. Simulation studies are used to compare the empirical likelihood methods and the normal approximation methods in terms of coverage accuracy. It is found that the empirical likelihood methods provide better inference.