A property of the relative subcodes

The relative subcodes are closely related to the concept of the relative generalized Hamming weight. Using projective geometry methods and the concept of the relative generalized Hamming weight, the authors prove a property of the relative subcodes which substantially improves the existing result.     

多目标线性规划的一种矩阵对策方法

提出了一种求解多目标线性规划问题的人机对话方法，其基本原理与ＳＴＥＭ方法大致相同，但采用了两人零和混合对策思想确定Ｔｃｈｅｂｙｃｈｅｖ距离中的相对权重，使权重的确定方法较传统的机械式相对固定权重确定方法更为合理     

Generalized ordered weighted averaging operators based method for MADM in intuitionistic fuzzy set setting

Multiattribute decision making (MADM) problems, in which the weights and ratings of alternatives are expressed with intuitionistic fuzzy (IF) sets, are investigated. Firstly, the relative degrees of membership and the relative degrees of non-membership are formulated as IF sets, the weights and values of alternatives on both qualitative and quantitative attributes may be expressed as IF sets in a unified way. Then a MADM method based on generalized ordered weighted averaging operators is proposed. The proposed method is illustrated with a numerical example.     

Intuitionistic fuzzy hierarchical clustering algorithms

Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.     

基于 ITFN 信息关联输入的改进群体 MULTIMOORA 决策方法

提出基于直觉梯形模糊数(intuitionistic trapezoidal fuzzy number, ITFN)极小、极大期望值的序关系判别准则, 并引入风险系数构建ITFN相对完善的带有决策者风险偏好的运算规则, 在此基础上定义直觉梯形模糊Bonferroni (intuitionistic trapezoidal fuzzy Bonferroni, ITFB)平均算子, 验证其相关性质. 针对决策者之间、属性之间分别存在关联关系且权重均未知的多属性群决策问题, 提出基于ITFN信息关联输入的改进群体MULTIMOORA决策方法. 首先, 构建直觉梯形模糊决策矩阵序列, 予以标准化处理, 并将其转化为极小期望决策矩阵序列; 其次, 综合利用基于熵权法和考虑决策者偏好关联的基于2-可加模糊测度与Choquet积分联合的主客观赋权法确定决策者权重及属性权重; 最后, 分别引入WITFB平均算子及ITFN的Hamming 距离以改进传统MULTIMOORA决策方法, 基于优势理论可对方案展开综合排序以确定最优方案. 通过算例分析验证本文方法的可行性及有效性.     

基于直觉模糊λ-Shapley Choquet积分算子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,即直觉模糊λ-Shapley Choquet积分算子TOPSIS的多属性群决策方法.首先,定义了直觉模糊λ-Shapley Choquet积分算子Hamming距离,并运用模糊测度,Choquet积分,Shapley值定义了直觉模糊算术广义λ-Shapley Choquet积分算子和直觉模糊几何广义λ-Shapley Choquet积分算子,并分析其有关性质;然后利用直觉模糊决策矩阵Hamming距离和记分函数和精确函数确定专家模糊测度和属性模糊测度;进而给出直觉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模糊TOPSIS方法的有效性.     

Induced and heavy aggregation operators with distance measures

This paper introduces a new aggregation model by using induced and heavy aggregation operators in distances measures such as the Hamming distance. It is called the induced heavy ordered weighted averaging (OWA) distance (IHOWAD) operator. This paper studies some of its main properties and a wide range of particular cases such as the induced heavy OWA (IHOWA) operator, the induced OWA distance (IOWAD) operator and the heavy OWA distance (HOWAD) operator. This approach is generalized by using generalized and quasi-arithmetic means obtaining the induced generalized IHOWAD (IGHOWAD) operator and the Quasi-IHOWAD operator. An application of the new approach in a decision making problem regarding the selection of strategies is developed.     

基于标准化区间权重向量的层次分析法研究

AHP(analytichierarchyprocess)的判断矩阵不满足一致性时 ,传统方法导出的权向量只能近似反应排序结果 ,有时甚至可能出错。针对这一问题 ,对传统的AHP进行了扩展 ,提出了具有标准化区间权重的层次分析法 ,结果更具柔性。首先通过建立线性规划模型求解判断矩阵的区间权向量 ,然后在分析以往通过区间数运算计算组合权重可能存在错误的基础上 ,再次通过建立线性规划模型 ,自下而上计算各方案相对于各指标的组合区间权重 ,计算结果比较合理。最后给出算例加以说明     

Some Generalized Single Valued Neutrosophic Linguistic Operators and Their Application to Multiple Attribute Group Decision Making

This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are obtained by using the entropy of neutrosophic linguistic sets. Then three generalized single valued neutrosophic linguistic operators are introduced, including the generalized single valued neutrosophic linguistic weighted averaging(GSVNLWA) operator, the generalized single valued neutrosophic linguistic ordered weighted averaging(GSVNLOWA) operator and the generalized single valued neutrosophic linguistic hybrid averaging(GSVNLHA) operator, and the GSVNLWA and GSVNLHA operators are used to aggregate information. Furthermore, similarity measure based on single valued neutrosophic linguistic numbers is defined and used to sort the alternatives and obtain the best alternative. Finally,an illustrative example is given to demonstrate the feasibility and effectiveness of the developed method.     

基于MVDR波束形成的FDA平台外干扰抑制

针对频控阵(frequency diverse array, FDA)在对与目标位置相近的平台外干扰进行抑制时, 传统FDA与非线性频偏结合不能实现距离-角度去耦合、对数递增FDA主瓣展宽较大和汉明窗加权FDA距离维旁瓣过高的问题, 在充分研究汉明窗加权的线性FDA(Hamming linear FDA, HL-FDA)方案的基础上, 对4种频偏方案的性能进行了分析, 提出采用FDA多输入多输出结构代替传统的一维均匀线性FDA结构, 通过结合最小方差无失真响应(minimum variance distortion free respinse, MVDR)准则, 将HL-FDA应用到MVDR自适应波束形成层面, 对平台外干扰进行抑制。仿真验证了HL-FDA在结合MVDR自适应波束形成算法后能有效地对抗距离-角度二维平台外干扰。     

Macwilliams Identities of Linear Codes over the Ring F_2+ uF_2+ vF_2

The Lee weight enumerators and the complete weight enumerators for the linear codes over ring R = F2 + u F2 + v F2 are defined and Gray map from Rnto F3n2 is constructed. By proving the fact that the Gray images of the self-dual codes over R are the self-dual codes over F2, and based on the Mac Williams identities for the Hamming weight enumerators of linear codes over F2, the Mac Williams identities for Lee weight enumerators of linear codes over R are given. Further, by introducing a special variable t, the Mac Williams identities for the complete weight enumerators of linear codes over R are obtained. Finally, an example which illustrates the correctness and function of the two Mac Williams identities is provided.     

一种动态综合评价方法及应用

将有序加权算子(OWA)及其相关算子推广到时序数据集结的方法中,提出了时序加权平均(TOWA)算子和时序几何平均(TOWGA)算子两种新的算子,并应用于动态综合评价方法中.同时介绍了TOWA和TOWGA算子加权向量(即时间权向量)的确定方法.最后,将该方法用于评价西部12省市在国家实施"西部大开发"战略后6年的宏观经济发展状况,结论验证了方法的有效性.     

基于离差的模糊多属性决策法及其应用

针对属性权重完全未知且属性值为三角模糊数的多属性决策问题,本文提出了一种基于线性规划和模糊向量投影的决策方法.该方法给出了三角模糊数向量投影、相对贴近度等概念.基于加权属性值离差最大化建立一个线性规划模型,通过求解此模型得到属性的权重,从而计算各方案的加权属性值在模糊正理想点和负理想解上的投影 ,进而计算相对贴近度,并据此对方案进行排序.最后,通过算例说明模型及方法的可行性和有效性.     

两类跳频序列集时频二维汉明相关性的分析

多普勒频移对现代扩频通信系统性能有着重要影响,设计跳频序列时需考虑具有时延和多普勒频移情形下序列的相关性。研究了跳频序列集时频最大周期汉明相关值的理论界,计算了Cai跳频序列集的时频二维周期汉明相关值,用该理论界检验了这类跳频序列集的二维周期汉明相关值,并进一步得到了部分达到最优的跳频序列;最后对多项式同余跳频序列集的二维周期汉明相关值进行了分析。     

Ordered weighted distance measure

The aim of this paper is to develop an ordered weighted distance （OWD） measure, which is the generalization of some widely used distance measures, including the normalized Hamming distance, the normalized Euclidean distance, the normalized geometric distance, the max distance, the median distance and the rain distance, etc. Moreover, the ordered weighted averaging operator, the generalized ordered weighted aggregation operator, the ordered weighted geometric operator, the averaging operator, the geometric mean operator, the ordered weighted square root operator, the square root operator, the max operator, the median operator and the rain operator are also the special cases of the OWD measure. Some methods depending on the input arguments are given to determine the weights associated with the OWD measure. The prominent characteristic of the OWD measure is that it can relieve （or intensify） the influence of unduly large or unduly small deviations on the aggregation results by assigning them low （or high） weights. This desirable characteristic makes the OWD measure very suitable to be used in many actual fields, including group decision making, medical diagnosis, data mining, and pattern recognition, etc. Finally, based on the OWD measure, we develop a group decision making approach, and illustrate it with a numerical example.     

QFD技术中各设计要求间依赖关系的线性规划处理

质量功能展开 (QFD)技术是一个多功能的计划工具 ,主要利用质量屋所含信息设计顾客满意的产品 .在已有文献的基础上 ,本文给出一个更加简单的线性规划模型 ,消除或减弱各设计要求间的依赖关系对设计要求的相对重要性的影响 ,所得结果可看作相互独立的参数且能用于下一阶段 ,即零件展开阶段 .     

Multi-attribute decision making model based on optimal membership and relative entropy

To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute decision making model is presented based on the optimal membership and the relative entropy. Firstly, the definitions of the optimal membership and the relative entropy are given. Secondly, for all alternatives, a set of preference weight vectors are obtained by solving a set of linear programming models whose goals are all to maximize the optimal membership. Thirdly, a relative entropy model is established to aggregate the preference weight vectors, thus an optimal weight vector is determined. Based on this optimal weight vector, the algorithm of deviation degree minimization is proposed to rank all the alternatives. Finally, a decision making example is given to demonstrate the feasibility and rationality of this new model.     

投资基金群决策风险-收益模型

投资基金是一种主要用于证券投资的大众化工具 ,其特点是募集社会公众投资者基金 ,委托具有专门知识和经验的专家经营操作 ,并将最终的收益分配给投资者 .本文综合考虑收益、风险和交易费用三个目标 ,讨论了含有无风险资产的证券组合投资问题 ;首先利用相对熵方法 ,将专家群体对目标和权重的建议水平及其偏好集结成群体偏好和目标 ,然后建立相应的目的规划 ,并将目的规划问题等价地转化为两个线性规划问题 ;给出了算例 .     

New approach to multiple attribute decision making with interval numbers

In an ambiguous decision domain, the evaluation values of alternatives against attributes would be interval numbers because of the inherent, uncertain property of the problems. By using a number of linear programming models, Bryson and Mobolurin propose an approach to compute attribute weights and overall values of the alternatives in the form of interval numbers. The intervals of the overall values of alternatives are then transformed into points or crisp values for comparisons among the alternatives. However, the attribute weights are different because of the use of linear programming models in Bryson and Mobolurin＇s approach. Thus, the alternatives are not comparable because different attribute weights are employed to calculate the overall values of the alternatives. A new approach is proposed to overcome the drawbacks of Bryson and Mobolurin＇s approach. By transforming the decision matrix with intervals into the one with crisp values, a new linear programming model is proposed, to calculate the attribute weights for conducting alternative ranking.     

Dynamic weighted voting for multiple classifier fusion:a generalized rough set method

1 .INTRODUCTIONMultiple classifier fusion or combination has prov-enitself a powerful tool for achieving high classifi-cation accuracy with moderately discri minatingclassifiers .If only output class labels are availablethe voting fusion[1]is often used as a decisionlevelfusion. However ,the main drawback of the votingfusion is that all classifiers are considered equallyreliable and this maylead to a confident decisiontobe changed by a less reliable classifier . A possibleway of overcomin…