基于区间直觉模糊集的供应商选择方法

提出一种基于区间直觉模糊集和TOPSIS法的供应商选择方法。给出了区间直觉模糊集的概念,定义了区间直觉模糊集之间的距离测度,在此基础上,将区间直觉模糊集和TOPSIS法相结合,提出了一种供应商选择的新方法,算例分析说明了该方法的有效性。     

直觉犹豫模糊集的相关系数在群推荐中的应用

在直觉犹豫模糊集描述的群推荐系统中,首先,针对直觉犹豫模糊距离公式计算相似性问题中存在的不足,提出了直觉犹豫模糊集相关系数的概念;其次,给出直觉犹豫模糊集相关系数的聚类算法,并分析采用直觉犹豫模糊集相关系数公式与距离公式计算相似性的区别;最后,利用直觉犹豫模糊集相关系数对电影进行推荐,结论表明了直觉犹豫模糊集相关系数方法的实用性和有效性。     

基于组合模型的直觉模糊集多属性决策方法

针对直觉模糊集是对模糊集理论的一种扩充,能够更好地处理模糊概念,研究了基于直觉模糊集的多属性决策问题.提出了直觉指数加权平均最大化和最小化组合模型,通过线性规划模型得到了属性的最优权重和相应的方案排序.数值例子表明,该方法是可行而有效的.     

Ⅱ-型模糊集截集的定义及特征研究

经典模糊集的截集概念是经典模糊集合与经典集合联系的桥梁,对于II-型模糊集,该文在分析II-型模糊集、区间值II-型模糊集、I-型模糊集以及经典集合之间关系的基础上,定义了II-型模糊集的截集概念,分析了II-型模糊集截集的特征,仿真证明了II-型模糊集截集的有效性,为基于II-型模糊集的决策、聚类等实际应用提供了新的方法。     

Nonstationary Fuzzy Sets

In this paper, the notion termed a “nonstationary fuzzy set” is introduced, and the concept of a perturbation function that is used for generating nonstationary fuzzy sets is presented. Definitions of the basic set operators (the union, the intersection, and the complement) for nonstationary fuzzy sets are given, together with proofs of selected properties of these operators. Two case studies were carried out in order to illustrate the use of nonstationary fuzzy sets in a nonstationary fuzzy inference, and to provide an initial insight into the relationships between nonstationary and interval type-2 fuzzy sets.      

Enhancing decision-making flexibility by introducing a new last aggregation evaluating approach based on multi-criteria group decision making and Pythagorean fuzzy sets

Uncertainty is an important factor in any decision-making process. Different tools and approaches have been introduced to handle the uncertain environment of group decision making. One of the latest tools in dealing with uncertainty is Pythagorean fuzzy sets (PFSs). These sets extend the concept of intuitionistic fuzzy sets. To show the advantages of these new sets, this paper offers a novel last aggregation group decision-making process for weighting and evaluating. The methodology employs a new approach in computing the weight of decision makers. Moreover, the concept of entropy is applied to address the fuzziness of weights of evaluation criteria in the process. The method develops a new index in ranking the alternatives. Finally, the proposed method is last aggregation, which means it will be more precise in situations with high variations in decision makers’ judgments. To show the applicability of the method, an example from the literature is adopted and solved for internet companies.     

区间直觉模糊粗糙集

将模糊粗糙集推广到区间直觉模糊粗糙集,基于区间直觉模糊等价关系和两个论域之间的一般区间直觉模糊关系,给出了区间直觉模糊粗糙集模型的不同形式,并讨论了一些相关性质。     

Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets

In this paper, we present a new method to deal with fuzzy multiple attributes group decision-making problems based on ranking interval type-2 fuzzy sets. First, we propose a new method for ranking interval type-2 fuzzy sets. Then, we propose a new method for fuzzy multiple attributes group decision-making based on the proposed ranking method of interval type-2 fuzzy sets. We also use some examples to illustrate the fuzzy multiple attributes group decision-making process of the proposed method. The proposed method is simpler than the methods presented in [Chen and Lee, 2010a] and [Lee and Chen, 2010b] for fuzzy multiple attributes group decision-making based on interval type-2 fuzzy sets. It provides us with a useful way for dealing with fuzzy multiple attributes group decision-making problems based on interval type-2 fuzzy sets.     

Sharpness relation and decidable fuzzy sets

The concept of "decidability" for fuzzy sets is defined. We prove that there exist fuzzy sets which do not have a decidable "sharpened" version and fuzzy, sets which are not "sharpened" versions of decidable fuzzy sets.     

Intuitionistic fuzzy soft modules

Molodtsov (1999) initiated the concept of soft sets in [1]. Maji et al. (2003) defined some operations on soft sets in [22]. Akta? and Ça?man (2007) generalized soft sets by defining the concept of soft groups in [16]. After them, Sun et al. (2008) gave soft modules in [21]. In this paper, the concept of an intuitionistic fuzzy soft module is introduced and some operations on intuitionistic fuzzy soft sets are given. Finally, some of its basic properties are studied.     

二型直觉模糊集

二型模糊集和直觉模糊集都具有很强的实际应用背景.二型模糊集增强了系统处理不确定性的能力,直觉模糊集为解决人们判断问题所出现的犹豫信息提供了理论依据.本文在二型模糊集和直觉模糊集的基础上,给出了二型直觉模糊集的概念,证明了二型直觉模糊集是一型模糊集、直觉模糊集、区间值模糊集、区间值直觉模糊集的广义形式,讨论了二型直觉模糊集的基本运算和二型直觉模糊关系.最后,研究了基于二型直觉模糊理论的近似推理,并实例说明了二型直觉模糊集的实际应用背景.     

动态模糊（DF）数据集序列的极限及其性质

以动态模糊集合的分配定理及经典集合序列的极限为基础,建立DF数据序列的极限概念,讨论了极限的运算性质。     

模糊集间的语义关联度及其应用

本文提出了一种描述模糊集间近似程度的语义关联度概念,它不仅与模糊集论域元素的隶属度有关,而且考虑了论域元素间的语义近似程度,因此它比过去模糊数学中定义的各种距离和贴近度等概念更加精细地刻划了模糊集间的相似性,从而在人工智能和其它领域中可有广泛应用,文中列举了它在情报检索和正文分类等方面的应用实例。此外,论文还给了两种近似地计算语义关联度的算法。     

q阶犹豫模糊集及其在决策中的应用

定义q阶模糊集的数乘、算术、几何等基本运算,研究运算的性质.结合犹豫模糊集与q阶模糊集,提出q阶犹豫模糊集的概念,定义q阶犹豫模糊集的一些运算并研究基本性质,提出q阶犹豫模糊集的得分函数和精确函数,实现q阶犹豫模糊集的对比.基于q阶犹豫模糊集的基本运算法则,构建q阶犹豫模糊集的多属性群决策模型,并通过实例验证此决策模型的可行性和有效性.     

基于直觉模糊ART神经网络的群事件检测方法

描述了态势评估系统中的目标编群问题、目标群处理流程和群事件的检测。结合直觉模糊贴近度理论,构造了直觉模糊ART神经网络。设计了网络的运行机制和网络权值向量的学习机制。给出了一个具体实例,检验了直觉模糊ART神经网络的目标编群效果,为群事件检测提供了一条有效途径。     

犹豫模糊集的α-截集及其应用

经典截集是联系模糊集和清晰集的桥梁。犹豫模糊集作为经典模糊集的拓展,它的相关理论研究还不够深入,特别是它与经典Ⅰ型模糊集以及其他模糊集之间的关系还缺少讨论。通过分析犹豫模糊集与Ⅰ型模糊集、区间Ⅱ型模糊集之间的关系,引入了犹豫模糊集的α-截集的概念并讨论其性质,根据该截集推导出犹豫模糊集的分解（表示）定理和更普适的扩展原则。通过分析相关性质及仿真实例,说明了犹豫模糊集的截集概念的合理性,为犹豫模糊多属性决策和聚类分析等问题提供了新的方法。这些结果也极大丰富了犹豫模糊集的相关基础理论。     

General type-2 fuzzy rough sets based on \alpha -plane Representation theory

Rough sets theory and fuzzy sets theory are mathematical tools to deal with uncertainty, imprecision in data analysis. Traditional rough set theory is restricted to crisp environments. Since theories of fuzzy sets and rough sets are distinct and complementary on dealing with uncertainty, the concept of fuzzy rough sets has been proposed. Type-2 fuzzy set provides additional degree of freedom, which makes it possible to directly handle highly uncertainties. Some researchers proposed interval type-2 fuzzy rough sets by combining interval type-2 fuzzy sets and rough sets. However, there are no reports about combining general type-2 fuzzy sets and rough sets. In addition, the $\alpha $ -plane representation method of general type-2 fuzzy sets has been extensively studied, and can reduce the computational workload. Motivated by the aforementioned accomplishments, in this paper, from the viewpoint of constructive approach, we first present definitions of upper and lower approximation operators of general type-2 fuzzy sets by using $\alpha $ -plane representation theory and study some basic properties of them. Furthermore, the connections between special general type-2 fuzzy relations and general type-2 fuzzy rough upper and lower approximation operators are also examined. Finally, in axiomatic approach, various classes of general type-2 fuzzy rough approximation operators are characterized by different sets of axioms.     

时序犹豫模糊软集及其在决策中的应用

针对犹豫模糊软集的信息随着时间动态变化的情形,引入时间参数,将犹豫模糊软集推广为时序犹豫模糊软集。基于时序犹豫模糊软集的概念,定义了其基本的运算法则,分析对应的运算结果并讨论其运算性质。给出了时序犹豫模糊软集的一种决策方法,并通过实例表明了该方法的有效性与可行性。     

ivnpiv-Neutrosophic soft sets and their decision making based on similarity measure

In recent years, soft sets and neutrosophic sets have become a subject of great interest for researchers and have been widely studied based on decision-making problems. In this paper, we propose a new concept of the soft sets that is called interval-valued neutrosophic parameterized interval-valued neutrosophic soft sets (ivnpivn-soft sets). It is a generalization of the other soft sets such as fuzzy soft sets, intuitionistic fuzzy soft sets, neutrosophic soft sets, fuzzy parameterized soft sets, intuitionistic fuzzy parameterized soft sets, neutrosophic parameterized neutrosophic soft sets. Also, we proposed ivnpivn-soft matrices which are representative of the ivnpivn-soft sets. We then developed a decision-making method on the ivnpivn-soft sets and ivnpivn-soft matrices. Then, we proposed a numerical example to verify validity and feasibility of the developed method. Finally, the proposed method is compared with several different methods to verify its feasibility.

     

基于软区分矩阵的模糊软集决策方法及其应用

通过在模糊软集中引入水平软集,用软区分矩阵来处理决策问题。首先,利用模糊软集的水平软集,将模糊软集转化为经典软集。其次,在软集中引入软区分矩阵的概念,提出了一种基于软区分矩阵解决模糊软集的新算法来处理决策问题。最后,通过实例说明了该算法的可行性。