Parallel Newton two‐stage methods based on ILU factorizations for nonlinear systems

Parallel iterative algorithms based on the Newton method and on two of its variants, the Shamanskii method and the Chord method, for solving nonlinear systems are proposed. These algorithms are based on two‐stage multisplitting methods where incomplete LU factorizations are considered as a mean of constructing the inner splittings. Convergence properties of these parallel methods are studied for H‐matrices. Computational results of these methods on two parallel computing systems are discussed. The reported experiments show the effectiveness of these methods. Copyright © 2006 John Wiley & Sons, Ltd.     

两类五阶解非线性方程组的迭代算法

本文首先根据Runge-Kutta方法的思想,结合Newton迭代法,提出了一类带参数的解非线性方程组F(x)=0的迭代算法,然后基于解非线性方程f(x)=0的King算法,给出第二类解非线性方程组的迭代算法,收敛性分析表明这两类算法都是五阶收敛的.其次给出了本文两类算法的效率指数,以及一些已知算法的效率指数,并且将本文算法的效率指数与其它方法进行详细的比较,通过效率比率R_(i,j)可知本文算法具有较高的计算效率.最后给出了四个数值实例,将本文两类算法与现有的几种算法进行比较,实验结果说明本文算法收敛速度快,迭代次数少,有明显的优势.     

Measures of inconsistency and defaults

We introduce a method for measuring inconsistency based on the number of formulas needed for deriving a contradiction. The relationships to previously considered methods based on probability measures are discussed. Those methods are extended to conditional probability and default reasoning.     

基于单位分解积分的伽辽金无网格方法研究

数值积分是伽辽金无网格方法实施的一个重要环节,提出了一种适合于伽辽金无网格方法的单位分解积分技术．该积分技术建立在有限覆盖和单位分解基础之上,不需要对积分区域进行分解,具有较高的积分精度．并以无单元伽辽金方法为例,详细说明了基于单位分解积分的伽辽金无网格方法的实现过程．这样,在近似函数建立和数值积分过程中都不需要进行网格划分,从而形成一种“真正的”无网格方法．     

Wavelet based schemes for linear advection-dispersion equation

In this paper, two wavelet based adaptive solvers are developed for linear advection-dispersion equation. The localization properties and multilevel structure of the wavelets in the physical space are used for adaptive computational methods for solution of equation which exhibit both smooth and shock-like behaviour. The first framework is based on wavelet-Galerkin and the second is based on multiscale decomposition of finite element method. Coiflet wavelet filter is incorporated in both the methods. The main advantage of both the adaptive methods is the elimination of spurious oscillations at very high Peclet number.     

Method of equivalent differences for the neutron transport equation

For boundary value problems in neutron transport theory, numerical methods are described that are based on the reduction of these problems to systems of nonlinear algebraic equations. Techniques based on the theory of nonlinear positive operators in partially ordered spaces are used to establish major results concerning the existence and uniqueness of solutions and solution-finding methods.     

A comparison of methods for terminating polynomial iterations

Three methods of terminating polynomial root-finding iterations are compared, one based on explicit calculation of rounding errors, one based on differences in the iterates, and one based on different methods of calculating the polynomial. In extensive experiments with randomly generated polynomials, it was found that the simplest method (based on differences in the iterates) usually gives the lowest actual error in the root.     

多响应优化方法的比较和应用研究

本文对目前几种多响应优化的主要方法进行了分析和总结,考察了马氏距离法、多元损失函数法、满意度函数法、概率法以及双响应曲面等几种主要方法在多响应优化中的应用,并对实例的多响应的预测值和方差进行了优化,比较了这几种方法的优缺点。研究结果表明,满意度函数法和概率法在处理多响应优化过程中能够取得较好的优化效果。     

Algebraic Dirichlet-to-Neumann mapping for linear elasticity problems with extreme contrasts in the coefficients

The convergence of iterative based domain decomposition methods is linked with the absorbing boundary conditions defined on the interface between the sub-domains. For linear elasticity problems, the optimal absorbing boundary conditions are associated with non-local Dirichlet-to-Neumann maps. Most of the methods to approximate these non-local maps are based on a continuous analysis. In this paper, an original algebraic technique based on the computation of local Dirichlet-to-Neumann maps is investigated. Numerical experiments are presented for linear elasticity problems with extreme contrasts in the coefficients.     

线性无量纲化方法对比及反向指标正向化方法

线性无量纲化方法的对比及反向指标的正向化方法都是综合评价的重要研究内容。从指标差异信息的角度,以TOPSIS、基于街区距离的TOPSIS和线性加权综合法为例,基于理论推导和实证分析对比了常用的线性无量纲化方法,并提出了两种反向指标正向化方法。研究发现,对于线性加权综合法和TOPSIS,不同线性无量纲化方法下同一指标归一化极差的不同是导致排序结果存在差异的关键因素;本文提出的反向指标正向化方法,不仅可以保证正向化前后TOPSIS、基于街区距离的TOPSIS的评价值不变,也可以实现反向指标正向化后线性加权综合法与基于街区距离的TOPSIS在排序目的上的等效性。最后,本文提出了线性无量纲化方法和反向指标正向化方法的应用建议。     

两个基于不同张量乘法的四阶张量分解

提出了两个基于不同张量乘法的四阶张量分解. 首先, 在矩阵乘法的基础上, 定义第一种四阶张量乘法(F-乘), 基于F-乘提出了第一种四阶张量分解(F-TD). 其次, 基于三阶张量t-product给出了第二种四阶张量乘法(B-乘)和分解(FT-SVD). 同时, 利用两种分解方法, 分别给出两个张量逼近定理. 最后, 三个数值算例阐明提出的两种分解方法的准确性和可行性.     

Optimization based DC programming and DCA for hierarchical clustering

One of the most promising approaches for clustering is based on methods of mathematical programming. In this paper we propose new optimization methods based on DC (Difference of Convex functions) programming for hierarchical clustering. A bilevel hierarchical clustering model is considered with different optimization formulations. They are all nonconvex, nonsmooth optimization problems for which we investigate attractive DC optimization Algorithms called DCA. Numerical results on some artificial and real-world databases are reported. The results demonstrate that the proposed algorithms are more efficient than related existing methods.     

Lagrangian formulation of domain decomposition methods: A unified theory

Domain decomposition methods based on one Lagrange multiplier have been shown to be very efficient for solving ill-conditioned problems in parallel. Several variants of these methods have been developed in the last ten years. These variants are based on an augmented Lagrangian formulation involving one or two Lagrange multipliers and on mixed type interface conditions between the sub-domains. In this paper, the Lagrangian formulations of some of these domain decomposition methods are presented both from a continuous and a discrete point of view.     

Stopping functionals for Gaussian quadrature formulas

Gaussian formulas are among the most often used quadrature formulas in practice. In this survey, an overview is given on stopping functionals for Gaussian formulas which are of the same type as quadrature formulas, i.e., linear combinations of function evaluations. In particular, methods based on extended formulas like the important Gauss–Kronrod and Patterson schemes, and methods which are based on Gaussian nodes, are presented and compared.     

A comparison between a recursive method based on an inverse mechanical formulation and shape optimization for solving inverse form finding problems in isotropic elastoplasticity

In this paper we compare two methods, a recursive method based on an inverse mechanical formulation and a method based on a recursive shape optimization formulation, in order to solve inverse form finding problems in isotropic elastoplasticity. Both methods are succinctly presented and a numerical example is given. It was found that no difference could be found between the node coordinates on the undeformed configurations computed with both methods. However the convergence to the solution is faster with the recursive method based on an inverse mechanical formulation than with the method based on shape optimization. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On interval predictor-corrector methods

One can approximate numerically the solution of the initial value problem using single or multistep methods. Linear multistep methods are used very often, especially combinations of explicit and implicit methods. In floating-point arithmetic from an explicit method (a predictor), we can get the first approximation to the solution obtained from an implicit method (a corrector). We can do the same with interval multistep methods. Realizing such interval methods in floating-point interval arithmetic, we compute solutions in the form of intervals which contain all possible errors. In this paper, we propose interval predictor-corrector methods based on conventional Adams-Bashforth-Moulton and Nyström-Milne-Simpson methods. In numerical examples, these methods are compared with interval methods of Runge-Kutta type and methods based on high-order Taylor series. It appears that the presented methods yield comparable approximations to the solutions.     

An application of support vector machines to sales forecasting under promotions

This paper deals with sales forecasting of a given commodity in a retail store of large distribution. For many years statistical methods such as ARIMA and Exponential Smoothing have been used to this aim. However the statistical methods could fail if high irregularity of sales are present, as happens for instance in case of promotions, because they are not well suited to model the nonlinear behaviors of the sales process. In recent years new methods based on machine learning are being employed for forecasting applications. A preliminary investigation indicates that methods based on the support vector machine (SVM) are more promising than other machine learning methods for the case considered. The paper assesses the application of SVM to sales forecasting under promotion impacts, compares SVM with other statistical methods, and tackles two real case studies.     

电力系统黑启动决策方法比较研究

黑启动作为电力体系安全防御和事故后快速恢复的措施之一,其路径的合理选择对电力系统快速恢复供电具有重要意义。近年来,学者们从不同角度提出了多种黑启动方案决策方法,然而并没有实现各决策方法间的优劣比较。本文引入平均绝对偏差公式,设计了一种黑启动决策方法比较策略,实现了黑启动决策方法的量化比较。在所提比较策略基础上,对常用的黑启动权重确定方法和排序方法进行了实验分析,广东电网上的实验结果表明基于标准差权重和TOPSIS排序的黑启动决策方法具有最高的准确性。本文的价值在于：(1)提出了一种新的比较策略,使黑启动决策方法的量化比较成为可能;(2)通过大量实验确定了一种优化的黑启动决策方法,为后续黑启动决策研究提供了比较基准。     

Some Methods Based on the D-Gap Function for Solving Monotone Variational Inequalities

The D-gap function has been useful in developing unconstrained descent methods for solving strongly monotone variational inequality problems. We show that the D-gap function has certain properties that are useful also for monotone variational inequality problems with bounded feasible set. Accordingly, we develop two unconstrained methods based on them that are similar in spirit to a feasible method of Zhu and Marcotte based on the regularized-gap function. We further discuss a third method based on applying the D-gap function to a regularized problem. Preliminary numerical experience is also reported.