经方量化归经研究中的向量矩阵应用

在经方量化归经研究中发现,药物组成的归经量化问题,若以五维向量表示更能体现其药物的归经方向和归经比例.利用向量矩阵分析方法给出了方剂归经量化的一种全新的量化模型体系,并以此研究方剂归经的量化规律及其应用特点.     

灰关联的表现形式与点、斜关联量化方法的探讨

灰关联的传统量化方法及其分析应用十分普遍，但是有时也出现其量化结 果与实际不相吻合，原因何在呢？笔者认为在进行灰关联分析时，先得搞清楚 灰关联的表现形式与灰关联思想，然后对症下药地去寻找其量化方法．为此， 本文提出了探讨性的意见──点、斜关联的量化方法．通过实例验证，得到较 为满意的结果．     

综合处理专家意见的ZHBM方法

在专家意见的不确定性量化法的基础上,给出了不确定性量化值的运算,进而通过实例创立了综合处理专家意见的ZHBM方法.     

区间系统的量化混杂反馈镇定

量化反馈镇定是控制理论中一个重要的研究领域.近年来得到了很多深刻的结果.研究一类区间系统的量化反馈镇定.在一定条件下,采用放大缩小参数的方法,构造了量化控制律,使系统实现反馈镇定.     

离差最大化时基于交叉评价的多属性决策方法

针对属性权重完全未知,且评价系统内既有客观数据、又有主观因素的多属性决策问题,提出一种基于离差最大化和交叉评价的模糊多属性决策方法。该方法首先定义了最小交叉效率、最大交叉效率等概念,将量化指标用交叉评价方法进行处理;然后采用模糊综合评价方法评价非量化指标,并基于离差最大化思想确定权重;最后将模糊化处理之后的量化指标与非量化指标一起进行最终评价,建立离差最大化条件下基于交叉评价的模糊多属性决策模型。最后通过算例验证了方法的可行性及有效性。     

改进交叉评价DEA在模糊综合评价中的应用

借鉴对抗型交叉评价的思想,首先利用对抗型交叉评价DEA(数据包络分析)模型对模糊综合评价的量化指标进行评价,三角模糊化后将其作为模糊综合评价量化指标的输入与非量化指标数据合成进行二次评价,以此建构了一种基于对抗型交叉评价DEA的模糊综合评价方法.方法可从根本上解决已有评价方法中模糊量化结果的不确定性问题,使客观数据与主观因素并存的多属性决策更加可靠.最后,通过算例说明了方法的应用.     

定性评价的一种定量评判方法

本在模糊综合评判的基础上进一步用计算关联度的方法，将定性评价问题进行量化评判，提出了具体的量化方法和步骤，具有广泛的实用性。中附有计算实例供参考。     

DoS攻击下的网络控制系统基于量化的输出反馈控制

针对存在DoS攻击的网络控制系统,提出了一种新的量化结构,并设计了H_∞输出反馈控制器.在网络环境下,假设控制器到执行器的传输通道中存在DoS攻击,采用新的量化结构对传感器信号进行量化处理,减少量化误差.通过将DoS攻击描述为服从Bernoulli分布的概率模型,把网络控制系统建模为具有随机参数的线性离散系统.在分析系统稳定性时,区别于普通二次型Lyapunov函数,本文选取了一种依赖量化误差及攻击概率的Lyapunov函数.基于稳定性理论和线性矩阵不等式方法,给出使闭环系统为均方意义下指数稳定且满足给定H_∞性能指标的输出反馈控制器设计方法.最后通过仿真算例,验证了所提方法的有效性.     

序信息系统中的双量化决策粗糙集模型

决策粗糙集和程度粗糙集作为两类广义的粗糙集模型,分别从相对信息量化和绝对信息量化的观点对经典的粗糙集模型进行了扩张。本文在序信息系统中将这两类广义粗糙集模型进行融合,即将决策粗糙集和程度粗糙集的近似算子重新组合,以此构造了两种不同类型的双量化粗糙集模型。然后,对模型的一些基本性质进行了讨论,新建立的粗糙集模型包含了相对量化信息和绝对量化信息。最后,通过对实际案例分析展现了双量化决策规则的获取方法,结果表明两类模型均可以有效的获取决策规则,本文为序信息系统中的决策分析提供了新的选择。     

一种针对实验数据的裕量和不确定性量化方法

针对基于k系数的裕量和不确定性量化方法只适用于正态分布的实验数据的局限性,文章分析了系统性能特征分位数与裕量和不确定性量化评估所关注的问题之间的联系,通过分位数回归求解指定的性能特征分位数及其置信限,实现了对实验数据的裕量和不确定性量化评估.新的评估方法对数据的分布形式及方差一致性没有要求,具有较强的数据适应性.示例分析对此进行了说明.     

牛顿迭代法与几种改进格式的效率指数

研究牛顿迭代、牛顿弦截法以及它们的六种改进格式的计算效率,计算了它们的效率指数,得到牛顿迭代、改进牛顿法、弦截法和改进弦截法(即所谓牛顿迭代的P.C格式)、二次插值迭代格式、推广的牛顿迭代法、调和平均牛顿法和中点牛顿法的效率指数分别为0.347/n、0.3662/n、0.4812/n、0.4812/n、0.347/n、0.3662/n、0.3662/n、0.3662/n.我们的结果显示,利用抛物插值多项式推出的迭代格式和改进弦截法并没有真正提高迭代的计算效率.此外,我们还证明了改进弦截法与牛顿弦截法等价,并利用这一结论给出了改进弦截法收敛阶为2.618的一个简化证明.     

用不确定德尔菲法预测GDP

德尔菲法是一种建立在专家意见基础上的预测评估方法.不确定统计是利用不确定理论收集和整理分析专家数据的一种统计方法,其中关键的一点是如何构造不确定变量的不确定分布.把德尔菲法和不确定统计相结合,就得到了一种估计不确定分布的新方法——不确定德尔菲法.对该方法的估计误差进行了改进,得到了一种预测GDP的新方法,并利用其预测邯郸市的生产总值(GDP).     

研究伪随机数序列独立性的均匀偏度法

§1 引言 由具有在[0,1]上均匀分布的总体中产生的简单子样称为随机数序列,其中的每一样本称为随机数。所谓伪随机数序列,一般是指用数学递推公式所产生的随机数序列。如最常见的乘同余方法,它所产生的伪随机数序列就是对给定的正整数M和小于M的任意正整数初值β_1,用如下递推公式确定的:     

Linearized ridge-path method for function minimization

A modification based on a linearization of a ridge-path optimization method is presented. The linearized ridge-path method is a nongradient, conjugate direction method which converges quadratically in half the number of search directions required for Powell's method of conjugate directions. The ridge-path method and its modification are compared with some basic algorithms, namely, univariate method, steepest descent method, Powell's conjugate direction method, conjugate gradient method, and variable-metric method. The assessment indicates that the ridge-path method, with modifications, could present a promising technique for optimization.This work was in partial fulfillment of the requirements for the MS degree of the first author at Cairo University, Cairo, Egypt. The authors would like to acknowledge the helpful and constructive suggestions of the reviewer.     

On preconditioned Uzawa methods and SOR methods for saddle-point problems

This paper studies convergence analysis of a preconditioned inexact Uzawa method for nondifferentiable saddle-point problems. The SOR-Newton method and the SOR-BFGS method are special cases of this method. We relax the Bramble-Pasciak-Vassilev condition on preconditioners for convergence of the inexact Uzawa method for linear saddle-point problems. The relaxed condition is used to determine the relaxation parameters in the SOR-Newton method and the SOR-BFGS method. Furthermore, we study global convergence of the multistep inexact Uzawa method for nondifferentiable saddle-point problems.     

一种基于矩阵初等变换的Schmidt正交化方法

对向量组的Schmidt正交化法和合同变换法的关系进行了分析,指出Schmidt正交化法就是合同变换法中利用规范化初等变换后的一种特殊情况,由此给出一种基于矩阵初等变换的Schmidt正交化方法——Schmidt初等变换正交化法,以及这一方法在软件Matlab上实现的程序.     

大密度比和大压力比可压缩流的数值计算

将WENO方法、RKDG方法、RKDG方法结合原来的Ghost Fluid方法以及RKDG方法结合改进的Ghost Fluid方法,应用到大密度比和大压力比的单相流以及气-气、气-液两相流的数值计算,并对计算结果进行了比较分析．结果表明,与其它的方法相比,RKDG方法结合改进的Ghost Fluid方法得到了高分辨率的计算结果,可以捕捉到正确的激波位置,随着网格的加密,计算解收敛到物理解．     

A modified Hestenes–Stiefel projection method for constrained nonlinear equations and its linear convergence rate

The Hestenes–Stiefel (HS) method is an efficient method for solving large-scale unconstrained optimization problems. In this paper, we extend the HS method to solve constrained nonlinear equations, and propose a modified HS projection method, which combines the modified HS method proposed by Zhang et al. with the projection method developed by Solodov and Svaiter. Under some mild assumptions, we show that the new method is globally convergent with an Armijo line search. Moreover, the R-linear convergence rate of the new method is established. Some preliminary numerical results show that the new method is efficient even for large-scale constrained nonlinear equations.     

A new symmetric linear eight-step method with fifth trigonometric order for the efficient integration of the Schrödinger equation

On the basis of a classical symmetric eight-step method, an optimized method with fifth trigonometric order for the numerical solution of the Schrödinger equation is developed in this work. The local truncation error analysis of the method proves the decrease of the maximum power of the energy in relation to the corresponding classical method, which renders the method highly efficient. This is confirmed by comparing the method to other methods from the literature while integrating the equation. The superiority of the method is strengthened by the existence of a larger interval of periodicity of the new method in comparison to the corresponding classical method.     

Simultaneous estimation of thin film thickness and optical properties using two-stage optimization

In this work, we proposed the new method for estimation of the thickness and the optical properties of the thin metal oxide film deposited on a transparent substrate. The developed method uses only transmittance spectra measured. Our method is based on the two stage optimization where the thickness is determined in the outer stage and the optical properties are determined in the inner stage. The differential evolutionary algorithm is used in solving the formulated problem. The proposed method was illustrated in the case study of Titanium dioxide film deposited on a glass substrate. The results indicate that the thickness and the optical properties estimated agree well with the experiment. Moreover, we investigated robustness of the proposed method in the case of transmittance spectra containing noises. The data were modelled by adding random noises ranging between 0 and 30% to the transmittance spectra measured. It is seen that the proposed method has better robustness and performance than the existing method based on pointwise unconstrained minimization approach. In solving the estimation problem, the performance of the proposed method was also compared with the well-known Levenberg?CMarquardt method and single stage differential evolutionary method. The results indicate that the proposed method has better performance than Levenberg?CMarquardt method and single stage differential evolutionary method. Moreover, the proposed method is more robust to random noise than Levenberg?CMarquardt method and single stage differential evolutionary method.