相依重尾随机变量中偏差的充分必要条件

本文研究了实值扩展负相依(END)一致变尾随机变量的中偏差.在给出部分和中偏差的基础上,得到了一定条件下随机和中偏差成立的充分必要条件.     

WOD随机变量加权和的完全收敛性

宽象限相依变量(简称WOD变量)是一类包含独立变量,负相协变量(简称NA变量),负象限相依变量(简称NOD变量)和推广的负象限相依变量(简称END变量)在内的非常广泛的相依变量.本文利用WOD变量的Rosenthal型矩不等式和随机变量的截尾技术,在一般的条件下建立了WOD变量加权和的完全收敛性.所得结果推广了若干相依变量的相应结果.     

宽象限相依随机变量部分和的中偏差及其在保险中的应用

研究了控制变换尾分布的宽象限相依实值随机变量部分和的中偏差.相应于所得到的理论结果,进一步给出了在相依保险风险模型中的两个应用;一是在基于顾客到达过程的保险风险模型中,保险公司盈余的渐近估计;二是在复合更新风险模型中,有限时和无限时破产概率的一致渐近估计.     

重尾相依随机变量的随机加权和尾概率的渐近估计（英文）

令{X_k;k≥1}为一列实值随机变量,{θ_k;k≥1}为另一列与之独立的随机变量序列.假设{X_k;k≥1}为两两广义负象限相依且服从重尾分布,在{θ_k;k≥1}独立和相依条件下,本文得到了一些渐近估计.     

相依稳健t过程函数型ANOVA模型

随着数据的多元化和复杂化,函数型ANOVA模型已经被越来越多的学者研究并应用到各行各业.为了减弱模型对于离群值的敏感度,本文对于相依的多元响应变量提出了一种相依稳健t过程函数型ANOVA模型.为了刻画变量之间的相依性和保证协方差函数的正定性,本文引入了随机效应变量和卷积方法构造了一个协方差函数.另外,模型中引入了随机效应函数去描述研究对象的个体特征.统计性质,例如稳健性和信息相合性在本文中也得到了相应的研究,并通过数值模拟和实例分析来验证此模型的可行性.     

实序线性空间中用广义二阶锥方向导数刻画集值优化ε-全局真有效解

在实序线性空间中,利用ε-全局真有效点的性质,借助广义二阶锥方向邻接(相依)导数的定义,建立了不受约束集值优化问题ε-全局真有效元的二阶必要最优性条件,同时得到了受约束集值优化问题在ε-全局真有效解意义下的二阶充分最优性条件.     

随机权和最大值的一致估计及其在保险风险理论中的应用

对任意相依非负随机权, 获得了独立重尾随机变量加权和最大值的一致估计, 应用这些结果研究了离散时间风险模型中具有相依随机回报的破产概率问题.     

集值优化问题在Henig真有效解意义下的导数型最优性条件

给出实的赋范空间中集值映射的Henig真有效解集的一些性质,并利用集值映射的相依上图导数和集值映射的次微分给出了集值优化问题Henig真有效解的最优性条件的充要条件.     

负超可加相依样本密度函数核估计的相合性

本文研究负超可加相依样本的密度函数核估计相合性.利用负超可加相依序列的不等式与性质,获得了密度函数核估计的逐点相和性和一致相和性以及r阶矩相和性.     

连续型随机变量序列的一类强偏差定理

设｛犡狀,狀≥１｝是任意相依连续型随机变量序列,｛犅狀,狀≥１｝是实直线上的Ｂｏｒｅｌ集,犐犅狀（狓）是犅狀的示性函数．该文研究｛犐犅狀（犡狀）,狀≥１｝的极限性质,得到一类用不等式表示的强偏差定理,其偏差界依赖于样本点．     

The covariance of uncertain variables: definition and calculation formulae

Uncertainty theory as a branch of axiomatic mathematics has been widely used to deal with human uncertainty. The two commonly used numerical characteristics of uncertain variables, the expected value and the variance together with their mathematical properties have been discussed and applied to real optimization problems in an uncertain environment. As a further study, in this paper, we focus on the covariance and correlation coefficient of uncertain variables. The definitions and calculation formulae of covariance and correlation coefficient of two uncertain variables are suggested by means of their inverse distributions. Then we show that the correlation coefficient of uncertain variables is essentially a measure of the relevance of distributions of uncertain variables. Finally, the relation between variance and covariance is analysed and represented with some equalities and inequalities.     

Time response of structure with interval and random parameters using a new hybrid uncertain analysis method

Practical structures often operate with some degree of uncertainties, and the uncertainties are often modelled as random parameters or interval parameters. For realistic predictions of the structures behaviour and performance, structure models should account for these uncertainties. This paper deals with time responses of engineering structures in the presence of random and/or interval uncertainties. Three uncertain structure models are introduced. The first one is random uncertain structure model with only random variables. The generalized polynomial chaos (PC) theory is applied to solve the random uncertain structure model. The second one is interval uncertain structure model with only interval variables. The Legendre metamodel (LM) method is presented to solve the interval uncertain structure model. The LM is based on Legendre polynomial expansion. The third one is hybrid uncertain structure model with both random and interval variables. The polynomial-chaos-Legendre-metamodel (PCLM) method is presented to solve the hybrid uncertain structure model. The PCLM is a combination of PC and LM. Three engineering examples are employed to demonstrate the effectiveness of the proposed methods. The uncertainties resulting from geometrical size, material properties or external loads are studied.     

静力分析的一般随机摄动法

本文对向量值和矩阵值函数的不确定结构的静力响应和可靠性进行了研究。基于Ｋｒｏｎｅｃｋｅｒ代数和摄动理论导出了随机结构的有限元分析方法，随机变量和系统导数很方便地排列到２Ｄ矩阵中，给出了一般的数学表达式．     

Reliability analysis for devices subject to competing failure processes based on chance theory

This paper studies the reliability for devices subject to independent competing failure processes of degradation and shocks in an uncertain random environment. The continuous degradation is governed by an uncertain process, and external shocks arrive according to an uncertain random renewal reward process, in which the inter-arrival times of shocks and the shock sizes are assumed to be random variables and uncertain variables, respectively. The device reliability is defined as the chance measure that the uncertain degradation signals do not exceed a soft failure threshold L, and the uncertain random shocks do not cause the device failure. The device reliability is obtained by employing chance theory under four different shock patterns. Finally, a case study on a gas insulated transmission line is carried out to show the implementation of the proposed model.     

Uncertain bimatrix game with applications

In real-world games, the players are often lack of the information about the other players’ (or even his own) payoffs. Assuming that all entries of payoff matrices are uncertain variables, this paper introduces a concept of uncertain bimatrix game. Within the framework of uncertainty theory, three solution concepts of uncertain equilibrium strategies as well as their existence theorem are proposed. Furthermore, a sufficient and necessary condition is presented for finding the uncertain equilibrium strategies. Finally, an example is provided for illustrating the usefulness of the theory developed in this paper.     

Uncertain multiobjective traveling salesman problem

Traveling salesman problem is a fundamental combinatorial optimization model studied in the operations research community for nearly half a century, yet there is surprisingly little literature that addresses uncertainty and multiple objectives in it. A novel TSP variation, called uncertain multiobjective TSP (UMTSP) with uncertain variables on the arc, is proposed in this paper on the basis of uncertainty theory, and a new solution approach named uncertain approach is applied to obtain Pareto efficient route in UMTSP. Considering the uncertain and combinatorial nature of UMTSP, a new ABC algorithm inserted with reverse operator, crossover operator and mutation operator is designed to this problem, which outperforms other algorithms through the performance comparison on three benchmark TSPs. Finally, a new benchmark UMTSP case study is presented to illustrate the construction and solution of UMTSP, which shows that the optimal route in deterministic TSP can be a poor route in UMTSP.     

On the convergence of uncertain random sequences

In this paper, a useful inequality for central moment of uncertain random variables is proved. Based on this inequality, a convergence theorem for sum of uncertain random variables is derived. A Borel–Cantelli lemma for chance measure is obtained based on the continuity assumption of uncertain measure. Finally, several convergence theorems for uncertain random sequences are established.     

Uncertain random goal programming

Goal programming provides an efficient technique to deal with decision making problems with multiple conflicting objectives. This paper joins the streams of research on goal programming by providing a so-called uncertain random goal programming to model the multi-objective optimization problem involving uncertain random variables. Several equivalent deterministic forms are derived on the condition that the set of parameters consists of uncertain variables and random variables. Finally, an example is given to illustrate the application of the approach.     

Uncertainty quantification of multi-dimensional parameters for composite laminates based on grey mathematical theory

In order to perform uncertainty quantification of elastic mechanical properties for composite laminates with multi-dimensional parameters, this paper is to develop a novel quantification approach based on grey mathematical theory. Here, uncertain parameters are modeled as correlated interval variables by virtue of some limited experimental points. The developed method not only can eliminate big errors in experimental points, but also can estimate uncertain information including nominal values, uncertain intervals, auto and mutual uncertainties of elastic properties. Besides, it can give out feasible domains of mechanical properties when considering mutual uncertainties for uncertainty propagation analysis. The numerical examples are implemented to demonstrate the feasibility and availability of the developed method. The results show that the developed method can become an important and powerful tool for uncertainty quantification of composite laminates with mutual uncertainties.     

Order statistics of uncertain random variables with application to <Emphasis Type="Italic">k</Emphasis>-out-of-<Emphasis Type="Italic">n</Emphasis> system

Uncertain random variables are tools to deal with a mixture of uncertainty and randomness. A new concept of order statistics associated with uncertain random variables is proposed, and is applied to analyze k-out-of-n systems with uncertain random lifetimes. The chance distributions of order statistics of uncertain random variables are derived from the operational law of uncertain random variables. Finally, the reliability of k-out-of-n systems with uncertain random lifetimes is discussed.