基于最小参数区间集的不确定结构响应分析

考虑到实际工程问题中普遍存在不确定性,完成了针对工程结构从定量化到传播的完整不确定性分析过程．通过建立包含全部有限样本点的最小区间/超立方体域来描述不确定参数的变化范围;借助于最小区间参数集,开展了不确定结构传播分析的研究工作以确定其最有利/不利响应．此外,进一步就给出的区间分析方法同经典概率方法的相容性进行了分析和探究．采用2个数值算例很好地论证了所述方法的正确性和可行性．     

基于熵的不确定性敏感性分析

为确定影响维修保障信息分析结果不确定性的关键输入参数,提出一种基于熵的不确定性敏感性分析方法.首先分析了模型输出结果的不确定性的表现形式、度量方法、产生机制;其次基于条件熵思想给出分析不确定性的敏感性参数以及敏感性分析方法;然后,简单介绍了盲数理论在计算不确定性数据中的应用;最后,结合平均维修时间模型进行了案例研究,说明了基于熵的不确定性敏感性分析方法的可用性,并证明了不确定性敏感性分析与求导不能等同的结论.     

基于区间数偏好信息的专家群体共识性研究

针对群决策中基于区间数偏好信息的共识性问题,给出了一种新的分析方法.首先给出了有关区间数和区间数决策矩阵的定义及若干性质;然后.通过定义有关专家群体判断关于方案针对指标的落影函数和专家群体关于方案针对指标的重心值,给出了群决策中基于区间数决策矩阵的共识性的分析方法和非共识的调整方法.最后,通过一个算例说明给出的分析方法.     

区间有限元方法及其在抗滑稳定性分析中的应用

通过区间值函数和实值函数的关系探讨了区间相关性导致的区间扩张的问题,给出了保证区间计算获得足够精度的计算方法;提出了基于单元的子区间摄动有限元计算方法,并给出了提高计算效率的一些方法和获得较好计算精度时的子区间数目的近似计算公式．结合工程实例,基于单元的子区间有限元方法和抗滑稳定性分析方法给出了稳定性的区间范围,为更合理地估计和评价结构的抗滑稳定性提供一定的依据．     

一种基于序区间偏好信息的群决策分析方法

针对序区间偏好信息的群决策方案排序问题,本文提出了一种新的分析方法.首先,给出了序区间的有关定义及其性质;然后,通过定义专家群体判断关于方案在排序位置的期望可能度和专家群体判断关于方案的数学期望值,给出了序区间偏好信息的群决策方案排序方法.最后,通过一个算例说明了本文提出的分析方法。     

关于区间数决策矩阵的专家群体判断共识性研究

针对群决策中基于区间数决策矩阵形式偏好信息的专家群体判断共识性问题,提出了一种分析方法.首先,给出了有关区间数的定义及其运算法则;然后,通过定义有关区间数决策矩阵的区间数向量,给出了各个专家与专家群体判断的共识性分析方法,同时,也给出了基于区间数决策矩阵的专家群体判断共识性的判别方法.最后,通过一个算例说明了本文提出的分析方法.     

一种PROMETHEE Ⅱ权重的敏感性分析方法

以往MADM的敏感性分析主要研究的是使方案集排序稳定的参数区间。本文针对PROMETHEEⅡ方法的权重建立一种新的敏感性分析数学模型，利用经典的线性规划方法，求解使得某方案排序第一且变化最小的权重值，回答了权重超出稳定区间后排序改变方向的问题。在实际应用中，有利于帮助决策者及时调整权重，得到合理结果。     

基于敏感性的结构损伤识别中的噪声分析

针对基于振动测试的结构损伤识别方法很容易受到环境噪声干扰的问题,提出了一种新的噪声分析方法,并结合Monte Carlo 数值模拟技术研究了测量噪声对基于敏感性的损伤识别方法的影响．与普遍采用的摄动法不同,提出的方法直接由敏感性矩阵的Moore-Penrose广义逆推导得出．该方法不仅使得噪声分析过程更简洁而有效,并且能同时分析频率和振型噪声对于识别结果的影响．针对3种常用的基于敏感性的损伤识别方法,通过一个单层门式框架的仿真研究,表明了所提出的噪声分析方法的正确性和有效性．     

基于区间数决策矩阵的评判专家水平分析方法

在群决策分析中,如何评判专家水平是一个重要课题,针对群决策中基于区间数决策矩阵形式偏好信息的评判专家水平问题,提出了一种分析方法。首先,给出了有关区间数、专家群体区间数决策矩阵的定义及其决策矩阵的规范化方法;然后,通过定义专家与专家群体关于方案排序向量之间的偏差,给出了基于理想点法的区间数决策矩阵形式偏好信息的专家评判水平的分析方法。同时,利用聚类分析方法,给出了专家评判水平分类的判别方法;最后,通过一个算例说明给出的分析方法。     

不同先验分布下的后验分布确定土力学参数

岩土工程中各土层参数的取值是根据现场及室内试验数据,采用经典统计学方法进行确定的,但这往往忽略了先验信息的作用。与经典统计学方法不同的是,Bayes法能从考虑先验分布的角度结合样本分布去推导后验分布,为岩土参数的取值提供一种新的分析方法。岩土工程勘察可视为对总体地层的随机抽样,当抽样完成时,样本分布密度函数是确定的,故Bayes法中的后验分布取决于先验分布,因此推导出两套不同的先验分布:利用先验信息确定先验分布及共轭先验分布。通过对先验及后验分布中超参数的计算,当样本总体符合N(μ,σ2)正态分布时,对所要研究的未知参数μ和σ展开分析,综合对比不同先验分布下后验分布的区间长度,给出岩土参数Bayes推断中最佳后验分布所要选择的先验分布。结果表明:共轭情况下的后验分布总是比无信息情况下的后验区间短,概率密度函数分布更集中,取值更方便。在正态总体情形下,根据未知参数μ和σ的联合后验分布求极值方法,确定样本总体中最大概率均值μ_max和方差σ_max作为工程设计采用值,为岩土参数取值方法提供了一条新的路径,有较好的工程意义。     

一种基于决策者风险态度的区间数多指标决策方法

针对具有区间数的多指标决策问题，提出了一种新的决策分析方法。该方法的思路是：首先通过引入决策的风险态度因子将区间数决策问题映射为传统的点值决策问题。然后给出了基于TOPSIS的方案排序方法，最后通过对风险态度因子的不同取值可进行方案排序的灵敏度分析。     

Bounding the set of solutions of a perturbed global optimization problem

Consider a global optimization problem in which the objective function and/or the constraints are expressed in terms of parameters. Suppose we wish to know the set of global solutions as the parameters vary over given intervals. In this paper we discuss procedures using interval analysis for computing guaranteed bounds on the solution set. This provides a means for doing a sensitivity analysis or simply bounding the effect of errors in data.     

Exact bounds for the sensitivity analysis of structures with uncertain-but-bounded parameters

Based on interval mathematical theory, the interval analysis method for the sensitivity analysis of the structure is advanced in this paper. The interval analysis method deals with the upper and lower bounds on eigenvalues of structures with uncertain-but-bounded (or interval) parameters. The stiffness matrix and the mass matrix of the structure, whose elements have the initial errors, are unknown except for the fact that they belong to given bounded matrix sets. The set of possible matrices can be described by the interval matrix. In terms of structural parameters, the stiffness matrix and the mass matrix take the non-negative decomposition. By means of interval extension, the generalized interval eigenvalue problem of structures with uncertain-but-bounded parameters can be divided into two generalized eigenvalue problems of a pair of real symmetric matrix pair by the real analysis method. Unlike normal sensitivity analysis method, the interval analysis method obtains informations on the response of structures with structural parameters (or design variables) changing and without any partial differential operation. Low computational effort and wide application rang are the characteristic of the proposed method. Two illustrative numerical examples illustrate the efficiency of the interval analysis.     

Correlation propagation for uncertainty analysis of structures based on a non-probabilistic ellipsoidal model

Traditional non-probabilistic methods for uncertainty propagation problems evaluate only the lower and upper bounds of structural responses, lacking any analysis of the correlations among the structural multi-responses. In this paper, a new non-probabilistic correlation propagation method is proposed to effectively evaluate the intervals and non-probabilistic correlation matrix of the structural responses. The uncertainty propagation process with correlated parameters is first decomposed into an interval propagation problem and a correlation propagation problem. The ellipsoidal model is then utilized to describe the uncertainty domain of the correlated parameters. For the interval propagation problem, a subinterval decomposition analysis method is developed based on the ellipsoidal model to efficiently evaluate the intervals of responses with a low computational cost. More importantly, the non-probabilistic correlation propagation equations are newly derived for theoretically predicting the correlations among the uncertain responses. Finally, the multi-dimensional ellipsoidal model is adopted again to represent both uncertainties and correlations of multi-responses. Three examples are presented to examine the accuracy and effectiveness of the proposed method both numerically and experimentally.     

An interval algorithm for sensitivity analysis of coupled vibro-acoustic systems

Sensitivity analysis is a vital part in the optimization design of coupled vibro-acoustic systems. A new interval sensitivity-analysis method for vibro-acoustic systems is proposed in this paper. This method relies on only interval perturbation analysis instead of partial derivatives and difference operations. For strongly nonlinear systems, in particular, this methodology requires parameter variation over narrower ranges in comparison with other methods. To implement sensitivity analysis based on this method, the interval ranges of the responses of the vibro-acoustic system with interval parameters should first be obtained. Therefore, an interval perturbation-analysis method is presented for obtaining the interval bounds of the sound-pressure responses of a coupled vibro-acoustic system with interval parameters. The interval perturbation method is then compared with the Monte Carlo method, which can be taken as the benchmark for comparative accuracy. Two numerical examples involving sensitivity analysis of vibro-acoustic systems illustrate the feasibility and effectiveness of the proposed interval-based method.     

区间运算和静力区间有限元

用均值和离差两参数表征区间变量的不确定性,根据区间运算规则,论证了区间变量的运算特性.将区间分析和有限元方法相结合,提出了非概率不确定结构的一种区间有限元分析方法.将区间有限元静力控制方程中n自由度不确定位移场特征参数的求解归结为求解一2n阶线性方程组.实例分析表明文中方法是有效和可行的.     

Characterization of perturbed mathematical programs and interval analysis

Several authors have used interval arithmetic to deal with parametric or sensitivity analysis in mathematical programming problems. Several reported computational experiments have shown how interval arithmetic can provide such results. However, there has not been a characterization of the resulting solution interval in terms of the usual sensitivity analysis results. This paper presents a characterization of perturbed convex programs and the resulting solution intervals.Interval arithmetic was developed as a mechanism for dealing with the inherent error associated with numerical computations using a computational device. Here it is used to describe error in the parameters. We show that, for convex programs, the resulting solution intervals can be characterized in terms of the usual sensitivity analysis results. It has been often reported in the literature that even well behaved convex problems can exhibit pathological behavior in the presence of data perturbations. This paper uses interval arithmetic to deal with such problems, and to characterize the behavior of the perturbed problem in the resulting interval. These results form the foundation for future computational studies using interval arithmetic to do nonlinear parametric analysis.     

产品设计定型时MTBF置信区间的确定

本文从系统工程角度出发提出了一种依据 AMSAA模型利用同类或相似产品研制阶段试验数据通过最优化过程来确定时间环境折合系数的新方法 ,进而给出了产品设计定型时 MTBF置信区间的确定方法 ,为解决长期困扰设计定型中可靠性指标验证这一关键问题找到了一条途径 .最后给出了一个工程应用实例     

逆高斯分布变异系数和尺度参数的统计推断研究

构造了逆高斯分布中变异系数的广义枢轴量,给出了一种参数的区间估计方法,并与MOVOER(method of variance of estimates recovery)和Bootstrap方法进行比较;给出了多总体下尺度参数两两差的同时置信区间.模拟结果表明:在中、小样本情况下,所给的广义置信区间其覆盖概率接近置信水平,平均区间长度较短,优于MOVOER方法与Bootstrap方法;对于多总体下尺度参数两两差的同时置信区间,所给出的三种同时置信区间,其覆盖率在置信水平附近,具有良好的频率性质.