直觉模糊变换半群的积与覆盖关系

提出了直觉模糊变换半群的(全)直积,圈积,直觉模糊变换半群的覆盖的定义,利用代数的手段讨论了直觉模糊变换半群的积的结合性质,研究了直觉模糊变换半群的积的覆盖关系.     

完全正则半群的直觉模糊软子半群

将直觉模糊软集运用在完全正则半群上,给出了完全正则半群的直觉模糊软子半群的新概念,研究了它的一些相关性质及若干等价刻画。最后,讨论了完全正则半群的直觉模糊软子半群的同态像与原像的性质。     

关于半群的直觉模糊拟理想

给出了半群中直觉模糊拟理想的等价定义,研究了半群中直觉模糊拟理想的若干性质和刻画,并用直觉模糊拟理想刻画群,完全正则半群和群半格．     

直觉模糊有限状态机的积

利用代数方法给出直觉模糊有限状态机的直觉笛卡尔积、直觉直积、直觉限制直积、直觉圈积、直觉级联积构造方法,并且讨论了它们的代数性质,同时探讨了直觉模糊有限状态机的直觉限制直积的覆盖,级联积的可分离的,以及利用直觉模糊变换半群探索了直觉圈积的结合性.     

半群的带有限度(α,β)的直觉模糊双理想

给出了半群中带有限度(α,β)的直觉模糊双理想的概念,研究了半群中带有限度(α,β)的直觉模糊双理想的若干性质和刻画。     

直积群上几类直觉模糊子群及其投影

给出了直觉模糊子群的性质及其等价命题,并通过定义直觉模糊集的直积与投影,获得了直觉模糊直积群及直觉模糊投影子群,进而在直觉模糊标准子群的条件下,分别讨论了直积群上的直觉模糊正规子群、直觉模糊特征子群、直觉模糊共轭与其直觉模糊投影子群的关系.     

序半群的广义直觉模糊理想

介绍序半群中具有边界值(α,β)的直觉模糊左理想和直觉模糊双理想的概念,对其性质进行了探讨,并通过有边界值(α,β)的直觉模糊左理想和直觉模糊双理想,对左正则和正则序半群的特征进行了研究.     

一种新的粗糙集模型及其应用

提出了一种新的基于区间直觉模糊关系和区间直觉模糊数的粗糙集模型.首先,介绍了区间直觉模糊集,区间直觉模糊关系和区间直觉模糊数等概念.然后,利用区间直觉模糊关系和区间直觉模糊数定义了一种新的粗糙集模型,并给出一些基本性质.最后将该模型应用于临床诊断系统中.实例验证了该粗糙集模型的有效性和实用性.     

半群的(λ,μ)-Ω-直觉模糊内(双)理想

在模糊集的基础上,把直觉模糊集,Ω-模糊集相结合来研究半群,给出半群中(λ,μ)-Ω-直觉模糊内(双)理想的定义并研究它们的性质。在同态前提下,研究了(λ,μ)-Ω-直觉模糊内(双)理想的像与原像。最后在定义半群(S^Ω,?)的基础上,研究它上的(λ,μ)-直觉模糊内(双)理想与(λ,μ)-Ω-直觉模糊内(双)理想的关系。     

直觉模糊正规子群与直觉模糊商群

在直觉模糊子群的基础上 ,引入直觉模糊正规子群与直觉模糊商群概念 ,并讨论了它们的一些性质 ,最后研究了群同态下 ,直觉模糊正规子群的对应关系     

一种基于不完备直觉模糊信息的TOPSIS方法

多属性决策过程中,每个方案的属性值有时体现为由直觉模糊数所刻划的语言变量,通过定义直觉模糊数间的距离,首先提出了基于直觉模糊数的TOPSIS方法;其次,考虑到在实际问题中往往会遇到不完备直觉模糊信息的事实,提出一种将不完备直觉模糊数完备化的方法,并建立了基于不完备直觉模糊信息的TOPSIS方法,同时通过实例说明该方法的有效性以及在多属性决策中的应用.     

DELPHI法在直觉模糊综合评价中的应用研究

针对直觉模糊综合评价中直觉模糊数集的取值方法问题,采用改进评价指标的评语等级划分,并结合Delphi法进行打分,来得出直觉模糊综合评价中的直觉模糊数集.最后利用该方法进行了实例分析.     

区间值直觉模糊超子群

在K.Atanassov引进区间值直觉模糊集的基础上,给出了区间值直觉模糊超子群的定义,刻画了其特征结构,研究了这类区间值直觉模糊超群的同态像及原像等问题.同时,讨论了区间值直觉模糊超子群与区间值直觉模糊子群的关系.     

Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems

In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval-valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach.     

Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment

TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach.     

Multiple criteria decision making method based on normal interval‐valued intuitionistic fuzzy generalized aggregation operator

On the basis of the normal intuitionistic fuzzy numbers (NIFNs), we proposed the normal interval‐valued intuitionistic fuzzy numbers (NIVIFNs) in which the values of the membership and nonmembership were extended to interval numbers. First, the definition, the properties, the score function and accuracy function of the NIVIFNs are briefly introduced, and the operational laws are defined. Second, some aggregation operators based on the NIVIFNs are proposed, such as normal interval‐valued intuitionistic fuzzy weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy ordered weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy hybrid weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy weighted geometric averaging operator, normal interval‐valued intuitionistic fuzzy ordered weighted geometric averaging operator, normal interval‐valued intuitionistic fuzzy hybrid weighted geometric averaging operator, and normal interval‐valued intuitionistic fuzzy generalized weighted averaging operator, normal interval‐valued intuitionistic fuzzy generalized ordered weighted averaging operator, normal interval‐valued intuitionistic fuzzy generalized hybrid weighted averaging operator, and some properties of these operators, such as idempotency, monotonicity, boundedness, commutativity, are studied. Further, an approach to the decision making problems with the NIVIFNs is established. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. © 2015 Wiley Periodicals, Inc. Complexity 21: 277–290, 2016     

基于直觉模糊距离的群决策专家意见聚合分析

提出了一种基于直觉模糊距离来聚合专家个人意见为一个优化的群体意见一致度的新方法.首先,根据直觉模糊集的几何意义,定义了两个直觉模糊集之间的距离;然后,利用直觉模糊距离来聚合专家两两之间对备选方案意见的一致度,综合考虑每位专家的相对重要权重,得到专家群体对备选方案意见的综合一致度;最后通过一个具体实例来说明这种方法的具体应用及计算过程.