一类模糊决策的理性分析和探讨

模糊决策的理性是模糊决策理论的一个研究热点。以Banerjee决策函数为框架,通过构造合理性条件进一步探讨了模糊决策函数与传统理性条件之间的关系;对一类模糊集M(S,Q)进行了分析,结合相关条件分析与探讨了基于模糊集M(S,Q)的一类模糊决策的理性特征。研究结果可为模糊决策的理论研究提供一定的理论参考。     

加权线性支持向量分类机的数据扰动分析

加权线性支持向量分类机是数据挖掘的新方法.它对应于一个优化问题.针对加权线性支持向量分类机优化问题建立了数据扰动分析理论方法.具体地针对加权线性支持向量分类机的原始问题建立了数据扰动分析基本定理,定理可以得到加权线性支持向量分类机问题的解及决策函数对数据参数的偏导数,同时可以定量分析输入数据的误差以及数据各种变化对其解以及决策函数值的定量影响,可以回答加权线性支持向量分类机问题的稳定性问题和灵敏度分析问题.     

支持向量分类方法理论基础的改进

支持向量机是通过求解对偶问题来解决原始问题的.针对线性决策函数f(x)=(w·x)+b,我们指出了其原有的逻辑系统中的错误,并通过严格的证明,对其理论基础作了改进.而且,对于阈值b,我们给出了一个新的简洁计算公式.     

高维紧支撑正交对称的小波

基于仿酉矩阵的对称扩充方法,该文提出了一种尺度因子为3的紧支撑高维正交对称小波构造算法.即设φ(x)∈L~2(R~d)是尺度因子为3的紧支撑d维正交对称尺度函数,P(ξ)是它的两尺度符号,p_(0,v)(ξ)为P(ξ)的相位符号.首先提出一种向量的对称正交变换,应用对称正交变换对3~d维向量(p_(0,v)(ξ))_v,v∈E_d的分量进行对称化.通过仿酉矩阵的对称扩充,给出了3~d-1个紧支撑高维正交对称小波构造.这种方法构造的小波支撑不超过尺度函数的支撑.最后给出一个构造算例.     

某些包含最多纯净两因子交互效应2_Ⅲ~(m-(m-k))设计的一种构造方法(英文)

本文给出了构造包含最多纯净两因子交互效应2Ⅲm-(m-k)设计的一种方法.对于某些设计参数m和k,验证了所构造的设计包含纯净两因子交互效应的数量多于Tang et al.(2002)所构造的设计.并且所构造的设计都给出了格子点表示.     

某些包含最多纯净两因子交互效应2m-(m-k)Ⅲ设计的一种构造方法

本文给出了构造包含最多纯净两因子交互效应2m-(m-k)Ⅲ设计的一种方法.对于某些设计参数m和k,验证了所构造的设计包含纯净两因子交互效应的数量多于Tang et al.(2002)所构造的设计.并且所构造的设计都给出了格子点表示.     

拟阵Q6与W4可F-线性表示的构造

对拟阵Q6与W4可F-线性表示的构造进行了研究.用E(G)在R上的链群F0(G,R)表示G的圈拟阵M(G);用松弛拟阵M的极小圈超平面X的方法得到拟阵M'.得到主要结果为:(i)用链群表示了M(K4),M(W4);(ii)用松弛极小圈超平面的方法从M(K4)构造了Q6,从M(W4)构造了W4,找出了W4可线性表示的所有...     

出奇制胜——巧用构造法解数学问题

构造法是解决数学问题的一种重要方法 .在解决一些相关的数学问题时 ,如果能根据已知问题的结构和特征 ,通过对条件和结论的敏锐观察和联想 ,构造一定的数学模型完成解题 ,往往能起到出奇制胜的效果 .一、构造方程从问题中发现或者构造等量关系 ,适当地引入参量 ,寻找已知量和未知量之间的关系 ,构造方程解决 .例 1　 (江苏竞赛题 )已知ａ ,ｂ ,ｃ,ｄ是四个不同的有理数 ,且 (ａ +ｃ) (ａ +ｄ) =1 ,(ｂ +ｃ) (ｂ +ｄ) =1 ,求(ａ+ｃ) (ｂ +ｃ)的值 .此题构思巧妙、新颖 ,解题的思路较广 .若仔细观察 ,通过对两个已知条件即两个已知式子的分析…     

由可分组设计构造对称设计

本文提出了由一类可分组设计构造出对称设计的方法.注意到这类可分组设计的关联图对应着5类结合方案的关系图.本文利用该5类结合方案的商结合方案,由这类可分组设计构造对称设计,并举例说明了构造的具体过程.此外,提出了一种利用阵列由对称设计构造可分组设计的方法.在此基础上,证明了两个有对偶性质的可分组设计GDDDP(2,11;5;0,1)和GDDDP(2,16;6;0,1)不存在.     

某些包含最多纯净两因子交互效应$2_{\rm{III}}^{m-(m-k)}$设计的一种构造方法

本文给出了构造包含最多纯净两因子交互效应$2_{\text{III}}^{m-(m-k)}$设计的一种方法.对于某些设计参数$m$和$k$, 验证了所构造的设计包含纯净两因子交互效应的数量多于Tang et al. (2002)所构造的设计. 并且所构造的设计都给出了格子点表示.     

On the fuzzy team decision in a changing environment

This paper formulates a fuzzy team decision problem in a changing environment. The concept of a fuzzy set is introduced to formulate the team decision processes in a dynamic environment which contains fuzzy states, fuzzy information functions, fuzzy information signals, fuzzy decision functions and fuzzy actions.     

Application of multiroot decision diagrams for integer functions

New data structures for representation of integer functions and matrices are proposed, namely, multiroot binary decision diagrams (MRBDD). Algorithms for performing standard operations on functions and matrices represented by MRBDDs are presented. Thanks to the more efficient reuse of structural elements, representation by multiroot binary decision diagrams is more efficient than the widely used multiterminal binary decision diagrams (MTBDD). Experimental results are given, which show that multiroot binary decision diagrams are a promising alternative to multiterminal binary decision diagrams, in particular, in probabilistic verification, manipulation of probability distributions, analysis of Petri nets, and other computational models.     

On the risk-equivalence of two methods of randomization in statistics

For statistical decision problems, there are two well-known methods of randomization: on the one hand, randomization by means of mixtures of nonrandomized decision functions (randomized decision rules) in the game “statistician against nature,” on the other hand, randomization by means of randomized decision functions. In this paper, we consider the problem of risk-equivalence of these two procedures, i.e., imposing fairly general conditions on a nonsequential decision problem, it is shown that to each randomized decision rule, there is a randomized decision function with uniformly the same risk, and vice versa. The crucial argument is based on rewriting risk-equivalence in terms of Choquet's integral representation theorem. It is shown, in addition, that for certain special cases that do not fulfill the assumptions of the Main Theorem, risk-equivalence holds at least partially.     

Solving multi-level multi-objective linear programming problems through fuzzy goal programming approach

In this paper, two new algorithms are presented to solve multi-level multi-objective linear programming (ML-MOLP) problems through the fuzzy goal programming (FGP) approach. The membership functions for the defined fuzzy goals of all objective functions at all levels are developed in the model formulation of the problem; so also are the membership functions for vectors of fuzzy goals of the decision variables, controlled by decision makers at the top levels. Then the fuzzy goal programming approach is used to achieve the highest degree of each of the membership goals by minimizing their deviational variables and thereby obtain the most satisfactory solution for all decision makers.     

Stochastic maximum principle in the optimal control of water resources systems

This work deals with the optimal control of stochastic water resources systems by the discrete stochastic maximum principle. This method is successfully applied to find analytic optimal solutions for water resources systems receiving independent stochastic inflows. The purpose is to optimize linear or quadratic objective functions subject to constraints imposed both on the state and decision variables. Two types of objective functions, one expressed in terms of correlated benefit functions and the other consisting of state and decision variables, are considered.     

Multiperson decision-making based on multiplicative preference relations

A multiperson decision-making problem, where the information about the alternatives provided by the experts can be presented by means of different preference representation structures (preference orderings, utility functions and multiplicative preference relations) is studied. Assuming the multiplicative preference relation as the uniform element of the preference representation, a multiplicative decision model based on fuzzy majority is presented to choose the best alternatives. In this decision model, several transformation functions are obtained to relate preference orderings and utility functions with multiplicative preference relations. The decision model uses the ordered weighted geometric operator to aggregate information and two choice degrees to rank the alternatives, quantifier guided dominance degree and quantifier guided non-dominance degree. The consistency of the model is analysed to prove that it acts coherently.     

Monte Carlo simulation techniques for group decision making with incomplete information

In this paper we deal with group decision-making problems where several decision makers elicit their own preferences separately. The decision makers’ preferences are quantified using a decision support system, which admits incomplete information concerning the decision makers’ responses to the questions they are asked. Consequently, each decision maker proposes classes of utility functions and attribute weight intervals for the different attributes. We introduce an approach based on Monte Carlo simulation techniques for aggregating decision maker preferences that could be the starting point for a negotiation process, if necessary. The negotiation process would basically involve the decision maker tightening the imprecise component utilities and weights to output more meaningful results and achieve a consensus alternative. We focus on how attribute weights and the component utilities associated with a consequence are randomly generated in the aggregation process taking into account the decision-makers’ preferences, i.e., their respective attribute weight intervals and classes of utility functions. Finally, an application to the evaluation of intervention strategies for restoring a radionuclide contaminated lake illustrates the usefulness and flexibility of this iterative process.     

基于属性间交互作用指标的多属性决策方法

多属性决策问题的各属性之间通常存在关联,而这种关联对决策的影响不可以忽略。基于属性间的交互作用指标,本文提出了一种新的评价函数,并研究了该评价函数的性质。首先,本文详细介绍了合作对策中几个常用的交互作用指标的概念。然后,提出了基于属性间交互作用指标的交互加权评价函数,简称为IWE函数。同时,本文给出了IWE函数的相关性质,并讨论了IWE函数与Choquet积分算子的联系与区别。最后,以算例验证本文所提方法在多属性决策中的合理性与有效性。     

基于错误逻辑分解转化联结词的生态文明指标知识表达模型研究

研究错误逻辑的知识表达模型,以错误逻辑理论结合生态文明"五位一体"所构建的生态文明建设指标体系,进行基于对象识别的知识表达.指标体系内的各元素分别被定义为错误逻辑模型中的事物、特征、函数和规则.建模时,首先进行事物分解,第二步进行特定事物下对应的特性及规则分解,最后根据判别规则G对错误函数f形式的影响,对各项指标所适用的错误函数类型进行分类.对象的生成可以为用矩阵这样的数据结构对逻辑知识进行系统化组织做前期准备.