Extension of TOPSIS to determine weight of decision maker for group decision making problems with uncertain information

In traditional TOPSIS method, the ideal solutions for alternatives are expressed in vectors. An important step in the process of group decision making is to determine the relative importance of each decision maker. In this paper, the weights of decision makers derived from individual decision are determined by using an extended TOPSIS method with interval numbers. The ideal decisions for all individual decisions are expressed in matrices. The positive ideal decision is the intersection of all individual decisions; the negative ideal decision is the union of all individual decisions. Comparisons with other methods are also made. A numerical example is examined to show the potential applications of the proposed method.     

群组决策系统的熵模型

应用拓展熵的概念研究了群组决策支持水平,个体决策可靠性理论及其应用问题,得到“水平”和“可靠性”测度的一系列公式和算法,从而开辟了群组和个体决策支持系统优化的新途径。     

基于直觉梯形模糊TOPSIS的多属性群决策方法

提出一种改进的逼近理想解排序(TOPSIS)方法,即直觉梯形模糊TOPSIS多属性群决策方法。首先,应用直觉梯形模糊数形式表示方案属性偏好和属性权重信息且专家权重完全未知;然后,利用直觉梯形模糊数间距离测度和期望值及直觉梯形模糊加权平均算子来确定决策者权重信息和属性权重信息;进而给出直觉梯形模糊环境下方案优选的算法;最后,通过算例进一步说明了该直觉梯形模糊TOPSIS方法的有效性。     

考虑QoS偏好的多属性群决策服务选择策略

面对多个功能相同或相似的服务,服务的Qo S是服务选择中重要的考虑因素.将Qo S属性分为精确数型、区间数型和三角模糊数型.在此基础上,利用TOPSIS（technique for order preference by similarity to an ideal solution）条件下的多属性群决策模型给出了服务选择过程,该过程考虑了多个决策者在决策过程中所占的权重,以及多个决策者不同的Qo S偏好权重.通过一个实例验证了该方法的有效性.     

群组通信的通用可组合机制

在通用可组合框架下研究群组通信问题.首先,作者在UC框架下分别提出群组通信模型的理想函数FSAGCOM、基于身份签密模型的理想函数FIDSC和群密钥分发模型的理想函数FGKD.其次,构造了UC安全的基于身份签密协议πIDSC,同时,证明了基于身份的签密协议πIDSC安全实现理想函数FIDSC当且仅当相应的基于身份的签密协议IDSC是安全的.最后,利用基于身份的签密协议πIDSC,提出了一种群组通信机制πSAGCOM,该机制在(FIDSC,FGKD)-混合模型下能安全实现群组通信的理想函数FSAGCOM.     

Semantic thresholding

The use of thresholding to separate objects in an image is analyzed in the light of a notion that ‘objects are in the eye of the beholder’, i.e. the existence of objects in an image is subjective rather than objective. Interpretation of the term ‘semantic’ as an association of an observed entity with an (other) entity which can be used for communication, is combined with Whorf's hypothesis on influence of language on reasoning, to yield a thresholding method. The method is based on minimizing the ambiguity which results from the different contexts (local and global) in which grey levels are classified as dark or bright. Examples are supplied and compared to thresholds which are optimal in the L₂ norm.     

合作伙伴选择的多准则群决策算法

针对合作伙伴选择问题,提出一种基于群体理想解的TOPSIS求解算法.求出对每个决策者而言各合作伙伴与其群体理想解的相对贴近度.基于备选合作伙伴集的群体理想解和负理想解,计算决策群体对各备选合作伙伴的最终排序.最后以一个供应商选择算例表明该方法的实用性.     

A model for evaluating computer network security systems with 2-tuple linguistic information

With respect to comprehensive evaluation model for computer network security with linguistic information and incomplete weight information, a new comprehensive evaluation model is proposed. In the method, the 2-tuple linguistic representation developed in recent years is used to aggregate the linguistic assessment information. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional TOPSIS, by which the attribute weights can be determined. Then, the optimal alternative(s) is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution (TLPIS) and on the other side the farthest distance of the 2-tuple linguistic negative ideal solution (TLNIS). The method has exact characteristics in linguistic information processing. It avoided information distortion and losing which occurred formerly in linguistic information processing. Finally, a numerical example of the evaluation of network security systems is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate.     

基于直觉模糊粗糙集相似度的多属性决策方法

将直觉模糊粗糙集应用于多属性决策问题,提出了基于改进的直觉模糊粗糙集相似度的多属性决策方法。针对现有的直觉模糊粗糙集相似度忽略犹豫度而造成度量不精确的问题,提出了一种改进的直觉模糊粗糙集相似性度量方法,并揭示其若干重要性质。在此基础上,将属性值用直觉模糊粗糙集表示,并通过各个方案与直觉模糊粗糙集正、负理想方案的相似度比较,实现决策方案排序。数值实例表明了该方法的可行性和有效性,其在态势评估、目标识别等信息融合领域有良好的应用前景。     

多属性决策的模糊理想点法

讨论了属性值为三角模糊变量的多属性决策问题,提出了确定模糊正理想点和模糊负理想点的方法,给出了基于模糊正理想点和模糊负理想点对各方案进行排序的方法。给出算例验证了所提出的方法的有效性,并验证了不同方法所确定的模糊正理想点和模糊负理想点,会导致方案排序的改变。     

群盲签名的通用可组合性研究

协议的UC安全性可以确保它在并发环境下运行的安全性。本文在UC框架下提出了一个群盲签名的理想函数,并在离散对数假设下构造了一个具有UC安全的群盲签名协议。然后,分析了此协议的安全性并详细地证明了群盲签名可以安全实现理想函数。     

群体偏好增强的混合群推荐方法

为减少评分数据稀疏性造成的群推荐精度损失,借助用户生成的项目属性特征,提出一种增强群体偏好的混合群推荐方法。一方面,针对用户-项目评分信息,采用协同过滤手段产生群推荐项目候选子集。另一方面,利用群体生成的项目属性分布特征,挖掘群体对项目属性的偏好,并以项目属性权重的方式融入到项目相似性计算中。通过聚类,产生反映群体偏好的项目集,将群体喜好的集合扩充到用于推荐的项目候选集中,实现群推荐项目候选集中群体偏好的增强。最后,从项目候选集中生成群推荐结果。将该方法应用大众点评网上餐厅的推荐,验证了项目属性特征对群推荐结果的积极影响。实验结果表明该方法在准确率和召回率上较经典群推荐方法都有大幅度提高。     

基于理想的协议安全性分析

1998年,Guttman等人提出了串空间理论作为一种新的密码协议形式化分析的工具.并在1999年第1次引入了关于消息代数上的理想以及诚实的概念来分析协议的保密性.由于理想结构的特殊性使得它可以刻画协议运行中消息之间的关系.利用理想的结构来分析协议的一些安全性质,例如保密性、认证性、零知识性以及如何抵抗猜测攻击.     

容许两个盘故障的磁盘阵列数据布局与图分解的条件和存在性研究

从一个新的途径讨论容许两个盘故障的磁盘阵列数据布局：把由数据单元和通过“异或”运算得到的校验单元组成的校验组用一个图表示，把校验组容许两个盘故障的阵列布局归结为校验组的单元集合的划分，进而转化为校验组的图的顶点和边组成集合的满足一定条件的分解．证明了校验组容许两个盘故障的单元集合划分的充分必要条件及存在性；讨论了优化阵列布局方案性能的条件；给出了阵列布局的步骤．从而为设计具有最优性能的容许两个盘故障的磁盘阵列数据布局方案提供了有效的途径．     

基于死区吸引律的离散重复控制

针对周期参考信号下的不确定离散时间系统,提出一种离散重复控制方法,利用死区函数设计新型的吸引律,将干扰补偿、抑制措施“嵌入”吸引律,构造理想误差动态,并基于此导出重复控制器。为了进行具体的控制器参数整定和表征闭环系统的误差动态行为,推导出了稳态误差带、单调减区域和绝对吸引层边界的表达式。所设计的离散重复控制器能够完全抑制周期对称干扰信号,控制器设计方法也适用于常值调节问题的定位控制。数值仿真及在电机伺服系统上的实验结果验证了所提出控制方法的有效性。     

Optimization‐based group performance deducing

Large‐scale group performance animation has been an important research topic because of its diverse range of applications including virtual rehearsal and film production. Animating hundreds of virtual actors as what the director wishes is a tough task. In this paper, we address this challenge by introducing an optimization method that generates large‐scale group performance by deducing a small‐scale one with fewer actors. We introduced group motion bigraph technique and transformed the motion‐deducing problem into a constrained optimization problem. A solving process is then presented to automatically obtain the motion of the large group with velocity constraints. Moreover, an interactive system of constructing the group motion bigraph has been implemented, which provides flexible edit and control on deducing group motion. The animation results show that our method is competent for deducing large‐scale group performance from only several motion clips performed by small groups. Copyright © 2013 John Wiley & Sons, Ltd.     

Ideals of an EMV-semiring

ABSTRACT

In this paper, congruences, ideals, and prime ideals of an EMV-semiring and of its associated EMV-algebra are studied. Then EMV-semirings are characterized and it is proved that each EMV-semiring can be embedded into a direct product of a family of MV-semirings as an EMV-semiring. Moreover, another representation of EMV-semirings are presented by EMV-semirings of continuous sections in a sheaf of commutative semirings whose stalks are localizations of EMV-semirings over prime ideals. Also, using the categorical equivalence between EMV-semirings and EMV-algebras, a representation of EMV-algebras are obtained.     

Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction

Case-based reasoning (CBR) solves many real-world problems under the assumption that similar observations have similar outputs. As an implementation of this assumption and inspired by the technique for order performance by the similarity to ideal solution (TOPSIS), this paper proposes a new type of multiple criteria CBR method for binary business failure prediction (BFP) with similarities to positive and negative ideal cases (SPNIC). Assuming that the binary prediction of business failure generates two results, i.e., failure and non-failure, we set the principle of this CBR forecasting method which is termed as SPNIC-based CBR as follows: new observations should have the same output as the positive or negative ideal case to which they are more similar. From the perspective of CBR, the SPNIC-based CBR forecasting method consists of R⁴ processes: retrieving positive and negative ideal cases, reusing solutions of ideal cases to forecast, retain cases, and reconstruct the case base. As a demonstration, we applied this method to forecast business failure in China with three data representations of a formerly collected dataset from normal economic environment and a representation of a recently collected dataset from financial crisis environment. The results indicate that this new CBR forecasting method can produce significantly better short-term discriminate capability than comparative methods, except for support vector machine, in normal economic environment; On the contrary, it cannot produce acceptable performance in financial crisis environment. Further topics about this method are discussed.