基于粗糙集分类的群决策专家个体可信度权重确定方法

提出了一种基于粗糙集分类来判断群决策专家个体可信度权重的新方法。先根据专家给出的判断矩阵分别按照条件属性值和决策属性值将方案进行分类,再用概率分布函数来考察每个条件属性类在决策属性类中的分布情况,算出与均匀分布时的概率分布函数的距离和,将各个专家判断矩阵的距离和进行归一化处理,以此作为群决策专家个体可信度的权值;最后用算例给出了该方法的可行性和有效性。     

AHP中群决策权重的确定与判断矩阵的合并

本首先运用系统聚类分析法，对群决策中的专家进行了分类，并为每位专家赋予了不同的权重。然后在专家自身权重的作用下，根据各个判断矩阵之间的一致性，算出每个判断矩阵的可信度权值，对经过一致性调整的多专家判断矩阵进行加权平均，得出多专家对各判定方案的判定结果。章的最后用一个算例来说明本中方法的实施过程。     

一种基于蒙特卡罗模拟的群体协商评价方法及其应用

针对综合评价中不同专家(或利益相关者)对属性权重看法不一致的情况,提出了一种蒙特卡罗模拟的群体协商评价方法。文章首先给出了一种专家影响力的确定方法;然后对各属性下专家的非一致性意见进行协商集结,得出属性权重的协商区间;最后在权重协商区间确定的基础上,利用蒙特卡罗模拟的方式来计算方案的优先排序概率,据此对方案进行排序,并给出了一个排序可信度的概念。文章最后给出了一个应用例。     

基于相对熵的多粒度语言判断矩阵的群决策方法

针对多粒度语言判断矩阵的群决策问题提出基于相对熵的最优化模型的排序方法.在多粒度语言偏好信息的导出函数基础上定义了语言判断矩阵对应的导出模糊互补判断矩阵,并给出其排序向量的计算式;同时采用语言判断矩阵的一致性指标来确定专家重要性程度的权向量;在相对熵的意义下构建了群决策排序向量的最优化模型,探讨了模型的求解方法.实例分析表明该模型是可行和有效的.     

基于粗糙集理论的相关关系预测方法研究

本基于粗糙集理论给出了对象与规则可信度的概念，提出了一种经济系统中相关关系预测法。利用信息熵的概念，评价因素的重要程度和约简因素，由此提取基本相关规则。在对象与规则之间的可信度基础上，建立了预测模型。与传统的回归预测法比较，这个方法不需要进行相关性判断、模型识别和检验，它直接从数据出发，在不损失信息的条件下约简冗余因素，寻找经济指标与影响因素之间的相关关系，能同时处理定性、定量因素以及不确定因素。算例计算说明了所提方法的有效性。     

一种群决策专家客观权重确定的改进方法

针对传统的群决策专家客观权重确定的两类主要方法(即基于判断矩阵一致性程度和基于专家排序向量或判断矩阵元素的聚类分析)的缺陷,提出了一种综合考虑两方面因素的改进方法.首先利用聚类分析方法根据各专家的排序向量得到专家类别间的权重,然后根据单个专家的判断矩阵一致性以及排序向量到类核心的距离确定最终权重.文末给出的算例表明该方法是可行、有效的.     

基于模糊熵的直觉模糊多属性群决策方法

针对专家权重未知、专家判断信息以直觉模糊集给出的多属性群决策问题,提出了一种新的决策方法.通过定义直觉模糊集的模糊熵计算专家判断信息的模糊程度,进而确定每位专家的权重.然后定义直觉模糊集的模糊交叉熵确定备选方案距理想方案和负理想方案的距离,再根据加权算术算子集结专家的判断信息,得到方案的排序.最后,通过一个实例分析验证了方法的有效性.     

基于可信度的统计检验决策研究

针对单侧假设检验中出现的自相矛盾的决策问题,在简单分析单侧假设检验两类错误具体形式的基础上,给出了检验决策可信度的概念及其计算公式,并提出了用决策可信度来判断单侧检验原假设及其结论是否有效的方法.实例表明,方法是可行的,有效的.     

基于熵权多目标决策的方案评估方法研究

给出了一种基于熵权多目标决策的方案评估方法.该方法在只有判断矩阵而没有专家权重的情况下,对有多个评价指标的方案评估问题,通过多对象关于多指标的评价矩阵的熵权计算,对多个合理方案进行优选评估,得出了可信度较高的优选方案,并将这一方法应用在航空装备维修费效益评价实例中.     

产品定级中挑选专家的数学模型

在工农业产品评定级别中，专家组的水平是至关重要的。文中给出一个挑选专家组成员的数学模型，可以检验专家对参评产品的决策水平，为评价所评结论的可信度提供参考依据。     

Determining attribute weights to improve solution reliability and its application to selecting leading industries

In multiple attribute decision analysis, many methods have been proposed to determine attribute weights. However, solution reliability is rarely considered in those methods. This paper develops an objective method in the context of the evidential reasoning approach to determine attribute weights which achieve high solution reliability. Firstly, the minimal satisfaction indicator of each alternative on each attribute is constructed using the performance data of each alternative. Secondly, the concept of superior intensity of an alternative is introduced and constructed using the minimal satisfaction of each alternative. Thirdly, the concept of solution reliability on each attribute is defined as the ordered weighted averaging (OWA) of the superior intensity of each alternative. Fourthly, to calculate the solution reliability on each attribute, the methods for determining the weights of the OWA operator are developed based on the minimax disparity method. Then, each attribute weight is calculated by letting it be proportional to the solution reliability on that attribute. A problem of selecting leading industries is investigated to demonstrate the applicability and validity of the proposed method. Finally, the proposed method is compared with other four methods using the problem, which demonstrates the high solution reliability of the proposed method.     

基于Markov的模块化电传操纵系统软件可靠性模型

电传操纵系统是影响飞行安全的关键系统,建立有效的电传操纵系统软件可靠性模型是软件可靠性测试和验证的基础.针对某型飞机系统安全性设计中横向通道电传操纵系统软件可靠性建模问题,建立了模块化的基于Markov的电传操纵系统软件可靠性模型.提出了综合考虑重要度和复杂度的软件可靠性指标分配方法,将可靠性目标分配到子模块.最后,通过实例验证了所建立的模型和指标分配方法的有效性.     

基于失效边数概率分布的K-终端网络重要度计算方法

重要度是现代网络薄弱环节识别的常用工具,其能量化网络不同的边对网络可靠性的影响程度。以往的K-终端网络重要度计算方法需已知网络边的可靠性以及边发生失效相互独立的条件,不能满足现实网络对于网络重要度计算的需求。鉴于此,为了突破这些条件的限制,本文在给定失效边数目的概率分布的背景下,发展K-终端网络重要度的计算方法,并提供一个十二面体网络的算例,验证了该计算方法的有效性和正确性。     

多台系统可靠性增长试验方法研究

提出了一种解决多台系统同步投试、同步停止试验和同步改进问题的新模型——指数模型．该模型充分考虑了增长过程中的各种可得信息,包括各改进阶段的失效数、未失效数和失效时间等数据．如果多台系统经过多次同步改进,并且单台系统的可靠性增长符合AMSAA模型,就可以合理地认为在每两个相邻的改进时刻之间,每台系统的失效时间服从指数分布．采用非参数方法得到多台系统在各同步停止试验时刻的可靠度,并利用最小二乘法拟合求得该模型中参数a和b的点估计值,以及参数b的置信限．通过在工程实例中对所提模型和几种已有模型计算结果的比较,说明了所提模型在解决多台系统同步可靠性增长问题中的合理性．     

基于边际效应分析的防空武器系统可靠性优化研究

针对复杂武器系统可靠性冗余分配优化问题,以系统的可靠度最大为目标函数,综合考虑系统的费用、质量等约束条件,建立了武器系统的可靠性冗余分配最优化模型;提出了基于相对增量的边际效应分析方法的求解算法,通过改进各级子系统的可靠性,从而使总的系统可靠性最大,最后对防空武器系统的可靠性冗余分配优化问题进行了实例分析。     

The cross-entropy method with patching for rare-event simulation of large Markov chains

There are various importance sampling schemes to estimate rare event probabilities in Markovian systems such as Markovian reliability models and Jackson networks. In this work, we present a general state-dependent importance sampling method which partitions the state space and applies the cross-entropy method to each partition. We investigate two versions of our algorithm and apply them to several examples of reliability and queueing models. In all these examples we compare our method with other importance sampling schemes. The performance of the importance sampling schemes is measured by the relative error of the estimator and by the efficiency of the algorithm. The results from experiments show considerable improvements both in running time of the algorithm and the variance of the estimator.     

A novel fractional moments-based maximum entropy method for high-dimensional reliability analysis

High-dimensional reliability analysis is still an open challenge in structural reliability community. To address this problem, a new sampling approach, named the good lattice point method based partially stratified sampling is proposed in the fractional moments-based maximum entropy method. In this approach, the original sample space is first partitioned into several orthogonal low-dimensional sample spaces, say 2 and 1 dimensions. Then, the samples in each low-dimensional sample space are generated by the good lattice point method, which are deterministic points and possess the property of large variance reduction. Finally, the samples in the original space can be obtained by randomly pairing the samples in low-dimensions, which may also significantly reduce the variance in high-dimensional cases. Then, this sampling approach is applied to evaluate the low-order fractional moments in the maximum entropy method with the tradeoff of efficiency and accuracy for high-dimensional reliability problems. In this regard, the probability density function of the performance function involving a large number of random inputs can be derived accordingly, where the reliability can be straightforwardly evaluated by a simple integral over the probability density function. Numerical examples are studied to validate the proposed method, which indicate the proposed method is of accuracy and efficiency for high-dimensional reliability analysis.     

An Iteration Method for Reliability Evaluation of a Fleet System

The fleet system considered here consists of n identical units (members) which are operated together under an operational program which specifies the schedule of the operation of the system and maintenance performed on the units in the system. Introduction of this operational program makes the reliability evaluation of the fleet system more realistic but complicated. A conventional Markov approach is effective only when a fleet system consists of a few units. This paper presents a new method for the reliability evaluation of a fleet system. This method reduces the problem of the reliability evaluation of the system to that of each unit by introducing a ‘utilization factor’. Therefore, the size of the problem is irrelevant to the number of the units in the system. An iteration method is used to obtain the unique solution of the problem.     

正态随机规划的确定性规划及其灵敏度分析

在大量的管理决策问题中,经常会遇到目标函数的系数和右端常数为相互独立的正态随机变量的随机线性规划模型.利用对偶规划将正态随机规划化为具有α可靠度的线性规划,给出了解决该正态随机规划的一个有效方法,并对正态随机变量的参数进行了灵敏度分析,避免了由于参数估计偏差给决策带来的风险,保证了最优方案的α可靠度.     

面向任务保障的多组件系统效益优化策略

为了保障系统在执行任务期间高可靠、高效益的运行,从系统效益的角度出发,构建了系统可靠性模型,采用边际效应思想构建了效益重要度,提出了一种面向任务保障的多组件系统效益优化策略。当系统可靠度下降到设定阈值时,计算系统各组件的效益重要度,选择效益重要度最大的组件进行备件分配,如此进行迭代,直到完成任务保障,形成最优的备件分配序列。通过该策略实现了以运行效益最优为目标,以系统可靠度和任务保障时长为约束的备件分配序列。最后,通过数值仿真验证了该策略的可行性。