确定模糊评价综合因素权重的一个方法

介绍引入三角模糊数判断矩阵以及将其转化为非模糊数判断矩阵的方法和步骤,说明它在确定模糊综合评价的因素权重时的作用和应用.最后进行实例分析.     

层次分析法权重计算方法分析及其应用研究

介绍层次分析法的基本概念,同时也分析了层次分析法权重的计算方法及应用,层次分析法的计算方法有四种方法:几何平均法、算术平均法、特征向量法、最小二乘法,以往的文献利用层次分析法解决实际问题时,都是采用其中的某一种方法求权重向量,不同的方法会导致结果有些偏差,将对一具体实例,采用四种计算方法分别得出权重向量再进行排序和综合分析,这样可以避免采用单一方法所产生的偏差,得出的结论将更全面、更有效。     

不确定型模糊判断矩阵一致性逼近与权重计算的一种方法

西方根据模糊判断矩阵一致性的定义，提出了区间数模糊判断矩阵一致性逼近与排序的方法：该方法充分利用区间数模糊判断矩阵信息构造一致性模糊判断矩阵进行一致性逼近，基于误差传递理论计算排序权重区间，最后给出了一个算例。     

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.     

空间计量模型中权重矩阵的类型与选择

根据空间效应产生起点及理论基础的不同,归纳了现有空间计量文献中邻接矩阵、反距离矩阵、经济特征矩阵以及嵌套矩阵等主要权重形式,并总结了其共同点、优缺点、演变脉络及使用注意事项.针对截面式权重矩阵本身面临的限制构造了两种必要的转换,即通过转换实现对不同地理区域之间空间效应的考察,以及从截面权重到面板权重的转换.最后指出研究者应该尽量采用多种新方法来确定空间权重形式以使其更客观.     

基于聚类的多属性群决策专家权重确定方法

对于多属性群决策中专家权重确定的问题,本文提出了基于聚类的专家权重确定方法,将专家权重分为类别间权重和类别内权重,对专家聚类步骤和类别间权重的计算方法进行了改进。通过专家给出的判断矩阵构建相容度矩阵,利用系统聚类原理,对相容度矩阵进行聚类,得到最大相容度谱系图。通过最大相容度间的距离和给定阈值的比较,对专家进行恰当分类,从而避免了根据现有研究步骤只能将专家分为两类的不足。此外,在确定类别间权重时,除继续对类容量较大的类赋予较大的类别间权重系数外,还引入专家判断矩阵的属性权重一致性来反映类别间的差异,从而有效避免了当某几类专家中含有相等数目专家时,赋予这几类专家相同类别间权重系数的问题。所提方法结构清晰、计算简便,并使得专家权重计算结果更为合理准确。最后运用一个算例对比验证了该方法的可行性和有效性。     

识别剪切位点的分组权重矩阵方法

提出识别剪切位点的分组权重矩阵方法．分组权重矩阵是一个子总体数未知的混合权重矩阵模型．为得到未知参数的极大似然估计,采用了EM方法,而子总体数是利用隙统计量确定的．作者给出了该方法的具体计算步骤．将该方法应用于人类和水稻基因组的供子和受子识别,并与现行的主要方法作了比较．结果表明,分组权重矩阵法的识别效果更为精确．     

对AHP单准则排序方法的改进

层次分析法(AHP)用两两比较的方法,通过构造比例标度判断矩阵为排序提供了一种合理的数据条件;对比例标度判断矩阵进行基于最大特征根的一致性检验,是为了把最大特征值对应的归一化特征向量作为排序向量;但终因理论上不能提供比例标度判断矩阵保序的充分条件,所以特征根排序法受到质疑,AHP需要改进.指出,改进AHP的正确途径是回归基于判断矩阵数据的排序方法研究.排序可行的条件是标度具有可加性;为此定义具有可加性的评分标度,建立标度转换公式将比例标度转换为评分标度;阐述为什么一致性检验无助于正确排序的原因并剖析为什么基于评分标度排序与一致性检验无关;由此建立基于评分标度判断矩阵中数据的评分排序方法.     

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。     

模糊判断矩阵排序向量的确定方法研究

首先给出模糊判断矩阵的两种一致性的定义。然后分析现有确定模糊判断矩阵排序向量的方法的特点及存在的问题，在此基础上，系统研究确定模糊判断矩阵排序向量的两类方法，第一类方法是先将模糊判断矩阵转化为AHP判断矩阵，然后将后者的排序向量作为前者的排序向量；另一类方法是直接由一致性或具有满意一致性的模糊判断矩阵计算排序向量。最后用算例说明所提出方法的应用。     

具有给定性质的奇偶因子

设G是一个图，g和f是定义在V（G）上的一整值函数且满足对于所有x∈V(G)均有g(x)≤f(x)以及g(x)≡f(x)(mod2)。称G的生成子图F为一个(g,g 2,…,f)－因子，如果对于一切x∈V(G)有degF(x)∈｛g(x),g(x) 2,…,f(x)｝，当g(x)＝1时（对于所有x∈V(G)，这样的因子称为（1，f）－奇因子。本文给出了一个图G具有（g,g 2,…,f)－因子和包含G中任意给定一条边的（1，f）－因子的充要条件，并据此，得到了一些有趣的结果。     

A Graphical Approach to Diagnosing the Validity of the Conditional Independence Assumptions of a Bayesian Network Given Data

Bayesian networks (BNs) have attained widespread use in data analysis and decision making. Well-studied topics include efficient inference, evidence propagation, parameter learning from data for complete and incomplete data scenarios, expert elicitation for calibrating BN probabilities, and structure learning. It is common for the researcher to assume the structure of the BN or to glean the structure from expert elicitation or domain knowledge. In this scenario, the model may be calibrated through learning the parameters from relevant data. There is a lack of work on model diagnostics for fitted BNs; this is the contribution of this article. We key on the definition of (conditional) independence to develop a graphical diagnostic that indicates whether the conditional independence assumptions imposed, when one assumes the structure of the BN, are supported by the data. We develop the approach theoretically and describe a Monte Carlo method to generate uncertainty measures for the consistency of the data with conditional independence assumptions under the model structure. We describe how this theoretical information and the data are presented in a graphical diagnostic tool. We demonstrate the approach through data simulated from BNs under different conditional independence assumptions. We also apply the diagnostic to a real-world dataset. The results presented in this article show that this approach is most feasible for smaller BNs—this is not peculiar to the proposed diagnostic graphic, but rather is related to the general difficulty of combining large BNs with data in any manner (such as through parameter estimation). It is the authors’ hope that this article helps highlight the need for more research into BN model diagnostics. This article has supplementary materials online.     

A Unified Approach to Shifts Induced by Right Invertible Operators

In this paper, shifts for a right invertible operator D induced by an analytic function acting in a linear complete metric space are considered. The case when these shifts coincide with the operator - valued function on a set which contains the set of all D-polynomials and the set of all exponentials is studied. It is shown that in this case these shifts are R-shifts and D-shifts (cf. [1], [10]).     

A Bootstrap Approach to Nonparametric Regression for Right Censored Data

In this paper a two-stage bootstrap method is proposed for nonparametric regression with right censored data. The method is applied to construct confidence intervals and bands for a conditional survival function. Its asymptotic validity is established using counting process techniques and martingale central limit theory. The performance of the bootstrap method is investigated in a Monte Carlo study. An illustration is given using a real data.     

Some Existence Theorems on Path Factors with Given Properties in Graphs

A path factor of G is a spanning subgraph of G such that its each component is a path.A path factor is called a P≥_n-factor if its each component admits at least n vertices. A graph G is called P≥_n-factor covered if G admits a P≥_n-factor containing e for any e ∈ E(G), which is defined by[Discrete Mathematics, 309, 2067–2076(2009)]. We first define the concept of a(P≥_n, k)-factor-critical covered graph, namely, a graph G is called(P≥_n, k)-factor-critical covered if G-D is P≥_n-factor covered for any D ? V(G) with |D| = k. In this paper, we verify that(i) a graph G with κ(G) ≥ k + 1 is(P≥2, k)-factor-critical covered if bind(G) 2+k/3;(ii) a graph G with |V(G)| ≥ k + 3 and κ(G) ≥ k + 1 is(P≥3, k)-factor-critical covered if bind(G) ≥4+k/3.     

一种合作研发风险因素识别方法

针对合作研发中的风险因素识别问题，本文提出了一种风险因素识别方法。首先构建了合作研发风险因素体系，然后在此基础上，考虑到专家针对风险因素之间的直接影响程度给出的语言区间判断信息，提出了一种考虑风险因素相互影响的合作研发风险因素识别方法，该方法是基于决策试验和评价实验室（DEMATEL）报告中的思想与方法，利用近年来发展的二元语义信息处理方法对语言区间判断信息进行处理和集结，进而对合作研发风险因素进行排序与归类。最后，通过一个算例说明了该方法的应用。     

关于企业经营者物质激励的几个问题

结合西方现代企业对经营者激励形式多样化的实际,提出我国的企业经营者要从目前“年薪制”激励为主转变为以股权激励为主,指出在进行外激励的同时,注重内激励的作用。同时调整激励报酬指标和标准,采取以“增长（值）率”而不是以“绝对额”同经营者报酬挂钩,以及只规定奖励幅度的办法,具体奖励标准由企业所有者根据经营难度和风险自定     

A Brief Note on the Approach to the Conic Sections of a Right Circular Cone from Dynamic Geometry

Nowadays there are different powerful 3D dynamic geometry systems (DGS) such as GeoGebra 5, Calques 3D and Cabri geometry 3D. An obvious application of this software that has been addressed by several authors is obtaining the conic sections of a right circular cone: the dynamic capabilities of 3D DGS allows to slowly vary the angle of the plane w.r.t. the axis of the cone, thus obtaining the different types of conics. In all the approaches we have found, a cone is firstly constructed and it is cut through variable planes. We propose to perform the construction the other way round: the plane is fixed (in fact it is a very convenient plane: \(z=0\)) and the cone is the moving object. This way the conic is expressed as a function of x and y (instead of as a function of x, y and z). Moreover, if the 3D DGS has algebraic capabilities, it is possible to obtain the implicit equation of the conic.     

Time to Sell a Given Quantity of Stock

The asymptotic behaviour of the time to sell a given quantity of stock depleted by a discrete demand process is derived for discrete time and continuous time (block depletion and continuous depletion).