常微分方程形式的M/M/1排队算子的谱分析

在l~1空间研究了常微分方程形式的M/M/1排队模型确定的算子A的谱问题.通过细致的谱分析,表明算子A的谱是一个椭圆型,椭圆内部点全是算子A的本征值.0位于椭圆的右边界点是边界上唯一的本征值,从而0不能与其它谱点相分离.这一结果表明常微分方程形式的M/M/1排队系统在有限时间不可能看到系统的稳定状态.     

二阶椭圆本征值问题Raviart-Thomas混合有限元法的误差分析

本文研究了一类本征函数及其梯度的对称二阶椭圆本征值问题的混合有限元法.利用对本征值、本征函数及其梯度的混合有限元误差,得到了本征函数及其梯度的L2(Ω)模和L∞(Ω)模估计.并且给出了数值算例,验证了理论分析.     

本征值Wilson非协调元近似的超收敛性与后验误差估计

本文给出二阶椭圆本征值问题Ｗｉｌｓｏｎ非协调元的超收敛与后验误差估计式,花很少代价就把Ｗｉｌｓｏｎ近似本征值的精度阶从ｈ＾２提高到ｈ＾４,并得到了渐近准确误差指示子。     

高阶椭圆算子Dirichlet本征值的下界

设Ω是R^m(m≥2）中的一个有界区域,其边界足够光滑,考察2p(p≥1）阶椭圆算子（－1）^p ∑│α│＝│β│＝pa^α(Aαβa^β)在Dirichlet边界条件下的本征值问题,给出了其本征值的一个下界,该下界除与维数m有关外仅依赖于区域Ω的体积。     

可修复人机储备系统算子的本征值问题

讨论了可修复人机储备系统算子的本征值问题,讨论了系统算子非零本征值的存在性,并且系统算子一个本征值对应一个本征向量.     

柔性臂中的一类本征值问题

本文研究单杆件柔性机器人操作手中出现的如下本征值问题(?)得到了本征值所满足的特征方程,据此研究了相应本征值的分布.此外还给出了本征函数之间的直交关系.最后给出了本征值计算结果,验证了上述理论分析的正确性.     

半简单本征值有限元外推

林群等的工作(见[1—3])奠定了本征值有限元外推的理论基础,证明了外推方法对简单本征值有效.本文要证明外推对半简单本征值也有效.由[1—3]的证明过程易知,只要证明存在λ_h,λ_(h/2)的本征函数 u_h,u_(h/2),它们都逼近λ的同一个本征函数 u 就可以了.但由于重本征值在离散化后一般被分离,给证明造成困难.本文提出了一个实施林群外推方法的新方案,巧妙地解决了这个问题.这方案花较少代价就能提高半简单本征值有限元近似解的精度阶.     

一般非均匀凸介质的迁移算子本征值的代数指标

本文讨论一般非均匀凸介质所确定的迁移算子的本征值的代数指标问题.利用我们探索的线性算子法,完整地解决了一般非均匀凸介质中迁移问题的实本征值的代数指标问题,证明了迁移算子的每个实本征值的代数指标均为1.     

基于WKBZ理论的耦合简正波-抛物方程理论

研究水平变化海洋环境中声传播的快速数值预报方法.在广义相积分(WKBZ)理论的基础上,提出了一种能够快速、准确地求解简正波本征值的方法,并将此方法应用于耦合简正波-抛物方程(CMPE) 理论.分析了两种典型声速剖面的简正波本征值,并计算了一个楔形海区中的声传播问题(JASA标准问题).计算结果表明本方法是一种快速而精确的数值方法.     

二维矩形域内Stokes流问题的辛解析和数值方法

给出了一种新的解析求解二维矩形域中的Stokes流动问题的方法——辛体系方法（Hamilton体系方法）．在辛体系下,基本问题归结为本征值和本征解的问题．由于辛本征解之间存在辛正交共轭关系,问题的解和边界条件均可以由本征解描述和表示．利用辛本征解空间的完备性,建立一套封闭的求解问题方法．研究结果表明零本征值本征解描述了基本流动,而非零本征值本征解则表示问题的局部效应．数值结果给出了几种有代表性的流动情况,显示了该求解方法对求解许多问题的有效性．同时,这种方法也为研究其他问题提供了一条思路．     

一个解凸二次规划的预测-校正光滑化方法

本文为凸二次规划问题提出一个光滑型方法,它是Engelke和Kanzow提出的解线性规划的光滑化算法的推广。其主要思想是将二次规划的最优性K-T条件写成一个非线性非光滑方程组,并利用Newton型方法来解其光滑近似。本文的方法是预测-校正方法。在较弱的条件下,证明了算法的全局收敛性和超线性收敛性。     

Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization

In this paper, a simulated-annealing-based method called Filter Simulated Annealing (FSA) method is proposed to deal with the constrained global optimization problem. The considered problem is reformulated so as to take the form of optimizing two functions, the objective function and the constraint violation function. Then, the FSA method is applied to solve the reformulated problem. The FSA method invokes a multi-start diversification scheme in order to achieve an efficient exploration process. To deal with the considered problem, a filter-set-based procedure is built in the FSA structure. Finally, an intensification scheme is applied as a final stage of the proposed method in order to overcome the slow convergence of SA-based methods. The computational results obtained by the FSA method are promising and show a superior performance of the proposed method, which is a point-to-point method, against population-based methods.     

A new hybrid method for solving global optimization problem

In this paper we present a new hybrid method, called the SASP method. The purpose of this method is the hybridization of the simulated annealing (SA) with the descent method, where we estimate the gradient using simultaneous perturbation. Firstly, the new hybrid method finds a local minimum using the descent method, then SA is executed in order to escape from the currently discovered local minimum to a better one, from which the descent method restarts a new local search, and so on until convergence.The new hybrid method can be widely applied to a class of global optimization problems for continuous functions with constraints. Experiments on 30 benchmark functions, including high dimensional functions, show that the new method is able to find near optimal solutions efficiently. In addition, its performance as a viable optimization method is demonstrated by comparing it with other existing algorithms. Numerical results improve the robustness and efficiency of the method presented.     

The Shell Method

<正>Here is another method for finding the volume of a solid of revolution.It's called the method of cylindrical shells or the shell method.For many problems,it's easier to apply than the disk method and washer method.So,what is a shell?A shell is a solid bounded by two concentric right circular cylinders(Figure 1).Some people also call it as a cylindrical shell.Shell method is always applied to a solid ob-     

无约束优化问题的对角稀疏拟牛顿法

对无约束优化问题提出了对角稀疏拟牛顿法,该算法采用了Armijo非精确线性搜索,并在每次迭代中利用对角矩阵近似拟牛顿法中的校正矩阵,使计算搜索方向的存贮量和工作量明显减少,为大型无约束优化问题的求解提供了新的思路．在通常的假设条件下,证明了算法的全局收敛性,线性收敛速度并分析了超线性收敛特征。数值实验表明算法比共轭梯度法有效,适于求解大型无约束优化问题．     

自适应多重网格法与超松弛法的比较

多重网格法(Multiple Grid Method,简称M-G方法)是近年来出现的快速方法之一,本文在M-G方法中采用自适应控制层间转换的技术,并将自适应M-G方法与G-S迭代方法及SOR迭代方,法进行了比较。其计算结果表明,自适应M-G方法的计算量比G-S迭代及SOR迭代少得多,当M-G方法所用层数为4-6层,这种优越性就更加明显,且自适应M-G方法中选取控制参数有很大的灵活性。     

自适应稀疏伪谱逼近新方法

自适应稀疏伪谱逼近法是广义混沌多项式类方法的最新进展,相对于其它方法具有计算精度高、速度快的优点.但它仍存在如下缺点：1）终止判据对逼近误差的估计精度偏低;2）只适用于单输出问题.本文提出了适用于多输出问题且具有更高逼近精度的自适应稀疏伪谱逼近新方法.本文首先提出了新型终止判据及基于此新型终止判据的自适应稀疏伪谱逼近新方法,并以命题的形式证明了新型终止判据相比于现有终止判据具有更高的估计精度,从而使基于此的逼近函数精度更接近于预期精度;进而,本文基于指标集的统一策略和新型终止判据,提出了适用于多输出问题的自适应稀疏伪谱逼近新方法,该方法因能充分利用各输出变量的抽样结果,具有比将单输出方法直接推广到多输出问题更高的计算效率.多个算例验证了本文所提出新方法的有效性和正确性.     

Finding roots of a real polynomial simultaneously by means of Bairstow's method

Aberth's method for finding the roots of a polynomial was shown to be robust. However, complex arithmetic is needed in this method even if the polynomial is real, because it starts with complex initial approximations. A novel method is proposed for real polynomials that does not require any complex arithmetic within iterations. It is based on the observation that Aberth's method is a systematic use of Newton's method. The analogous technique is then applied to Bairstow's procedure in the proposed method. As a result, the method needs half the computations per iteration than Aberth's method. Numerical experiments showed that the new method exhibited a competitive overall performance for the test polynomials.     

On the quadratic convergence of a generalization of the Jacobi Method to arbitrary matrices

A method of diagonalizing a general matrix is proved to be ultimately quadratically convergent for all normalizable matrices. The method is a slight modification of a method due to P. J. Eberlein, and it brings the general matrix into a normal one by a combination of unitary plane transformations and plane shears (non-unitary). The method is a generalization of the Jacobi Method: in the case of normal matrices it is equivalent to the method given by Goldstine and Horwitz.     

对称正定矩阵的多级迭代法

本文主要研究解对称正定矩阵的多级迭代法,并对其收敛性进行证明。最后用数值实验验证此方法的有效性．多级迭代法特别适用于并行计算,并且可以被理解为古典迭代法的扩展,或共轭梯度法的预处理子。