FI代数的模糊素MP滤子与模糊超MP滤子

将Zadeh提出的模糊集概念应用于FI代数,提出了FI代数的模糊素MP滤子和模糊超MP滤子的概念并研究其性质及相互关系。给出了满足一定条件的并半格FI代数的模糊素MP滤子的若干等价刻画并建立了模糊素MP滤子定理。获得了一个模糊集成为超模糊MP滤子的充要条件。     

R0代数中的模糊正规滤子

在R₀代数中引入模糊正规滤子的概念,给出其充要条件,得到了模糊正规滤子的扩张性质,讨论了模糊正规滤子与模糊滤子、截集之间的关系,最后,用模糊正规滤子刻画了正规R₀代数M和正规商R₀代数M/f。     

FI代数上的直觉模糊滤子和同余关系

在FI代数上引入直觉模糊滤子的概念,给出了直觉模糊滤子的一个等价刻画,探讨了由直觉模糊滤子诱导的同余关系,证明了一些性质。     

泛逻辑学中UB代数系统的fuzzy滤子

文献[2]给出了理想状态下泛逻辑学的形式演绎系统!,证明了此系统是可靠的。文献[3]提出了在理想状态(h=k=0.5)下泛逻辑学对应的代数系统-UB代数。文献[5]研究了泛逻辑学中UB代数系统的若干性质。在文献[3,5]的基础上,进一步讨论了UB代数fuzzy滤子与商代数。     

伪BL-代数的犹豫模糊滤子

提出了伪BL-代数的犹豫模糊滤子的概念，给出它的几个等价刻画，并研究了它的一些性质。进一步，引入了伪BL-代数的几种犹豫模糊滤子，如犹豫模糊Boolean滤子、犹豫模糊正规滤子、犹豫模糊超滤子和犹豫模糊固执滤子，讨论了它们的一些刻画，给出了其间的一些关系。通过研究伪BL-代数中犹豫模糊Boolean滤子与犹豫模糊正规滤子的关系，解决了伪BL-代数中是否每个Boolean滤子都是正规滤子这样一个开问题。     

NML代数的滤子及其结构

首先在NML代数上引入MP-滤子与素滤子的概念,进而讨论了滤子和素滤子的基本性质,最后在全体素滤子之集上建立了拓扑结构。     

BL-代数上的几种直觉模糊滤子

结合直觉模糊集和滤子理论,对BL-代数上的直觉模糊滤子进行了研究。首先回顾了BL-代数和直觉模糊集的有关基础知识。然后引入BL-代数上的直觉模糊滤子、直觉模糊格滤子、直觉模糊布尔滤子和直觉模糊蕴涵滤子的概念,讨论了它们的一系列重要性质,证明了直觉模糊滤子与直觉模糊格滤子、直觉模糊布尔滤子和直觉模糊蕴涵滤子是等价的,并用实例进行了验证。最后探讨了直觉模糊滤子和模糊滤子的关系。     

R0代数中的正蕴涵MP滤子和固执MP滤子

在R0代数中,给出布尔MP滤子的几种性质特征。提出正蕴涵MP滤子和固执MP滤子的概念,讨论了它们的一些性质定理。证明正蕴涵MP滤子与布尔MP滤子等价,固执MP滤子与MP超滤等价,同时也讨论了正蕴涵MP滤子和固执MP滤子的关系。     

Intuitionistic Fuzzy Filters of the BL-Algebras

结合直觉模糊集和滤子理论,对BL-代数上的直觉模糊滤子进行了研究.首先回顾了BL-代数和直觉模糊集的有关基础知识.然后引入BL-代数上的直觉模糊滤子、直觉模糊格滤子、直觉模糊布尔滤子和直觉模糊蕴涵滤子的概念,讨论了它们的一系列重要性质,证明了直觉模糊滤子与直觉模糊格滤子、直觉模糊布尔滤子和直觉模糊蕴涵滤子是等价的,并用实例进行了验证.最后探讨了直觉模糊滤子和模糊滤子的关系.     

BCK代数的区间值(∈,∈∨q)-模糊子代数

将Zadeh提出的区间值模糊集的概念应用于BCK代数,提出BCK代数的区间值(∈,∈∨q)模糊子代数的概念并研究其性质。给出了区间值模糊集成为区间值(∈,∈∨q)模糊子代数的充要条件;讨论了区间值(∈,∈∨q)模糊子代数与子代数以及(∈,∈∨q)模糊子代数间的关系;定义了区间值模糊集的象与原象,获得了区间值(∈,∈∨q)模糊子代数的象与原象成为区间值(∈,∈∨q)模糊子代数的条件。     

Algorithms for complex interval‐valued q‐rung orthopair fuzzy sets in decision making based on aggregation operators,AHP, and TOPSIS

The interval‐valued q‐rung orthopair fuzzy set (IVq‐ROFS) and complex fuzzy set (CFS) are two generalizations of the fuzzy set (FS) to cope with uncertain information in real decision making problems. The aim of the present work is to develop the concept of complex interval‐valued q‐rung orthopair fuzzy set (CIVq‐ROFS) as a generalization of interval‐valued complex fuzzy set (IVCFS) and q‐rung orthopair fuzzy set (q‐ROFS), which can better express the time‐periodic problems and two‐dimensional information in a single set. In this article not only basic properties of CIVq‐ROFSs are discussed but also averaging aggregation operator (AAO) and geometric aggregation operator (GAO) with some desirable properties and operations on CIVq‐ROFSs are discussed. The proposed operations are the extension of the operations of IVq‐ROFS, q‐ROFS, interval‐valued Pythagorean fuzzy, Pythagorean fuzzy (PF), interval‐valued intuitionistic fuzzy, intuitionistic fuzzy, complex q‐ROFS, complex PF, and complex intuitionistic fuzzy theories. Further, the Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) method are also examine based on CIVq‐ROFS to explore the reliability and proficiency of the work. Moreover, we discussed the advantages of CIVq‐ROFS and showed that the concepts of IVCFS and q‐ROFS are the special cases of CIVq‐ROFS. Moreover, the flexibility of proposed averaging aggregation operator and geometric aggregation operator in a multi‐attribute decision making (MADM) problem are also discussed. Finally, a comparative study of CIVq‐ROFSs with pre‐existing work is discussed in detail.     

基于中心扰动的区间值模糊集图像阈值分割算法

针对基于区间值模糊集的图像阈值分割问题,提出了一种基于中心扰动的区间值模糊集图像阈值分割算法.采用对目标及背景中心进行扰动的方式,考虑不确定、不精确信息对图像类别中心的影响,并利用限制等价函数构建图像的区间值模糊集模型;在提出一种区间值模糊集上区别度量的基础上建立目标函数来搜索最佳分割阈值.通过对三种类型的图像数据进行仿真实验,结果表明提出的方法在视觉和指标上总体得到了较好的结果,证明了该算法的有效性.     

基于区间值模糊集的理想化软BCK代数

将Zadeh提出的区间值模糊集概念应用于理想化软BCK代数问题的研究。借助于BCK代数的区间值模糊理想、区间值[(∈,∈∨q)]-模糊理想和区间值[(∈,∈∨q)]-模糊理想的概念,获得了一个给定的BCK代数上的几类特殊的理想化软BCK代数的若干等价刻画。     

基于OWA算子的区间值加权模糊推理

针对如何对区间值模糊产生式规则赋予合理权值的问题,将OWA算子引入到区间值模糊推理中。介绍一种基于OWA算子的区间值赋权方法,根据此方法给出区间值模糊集上的加权模糊产生式规则的推理算法。在采用该算法的过程中,为合理地计算输入事实与规则前件的匹配程度,引入基于OWA算子的区间值模糊匹配函数值和总体贴近度的计算方法。实例分析表明了所给出的区间值模糊推理算法的有效性和可行性。     

New exponential operational laws and their aggregation operators for interval‐valued Pythagorean fuzzy multicriteria decision‐making

In this article, we define two new exponential operational laws about the interval‐valued Pythagorean fuzzy set (IVPFS) and their corresponding aggregation operators. However, the exponential parameters (weights) of all the existing operational laws of IVPFSs are crisp values in IVPFS decision‐making problems. As a supplement, this paper first introduces new exponential operational laws of IVPFS, where bases are crisp values or interval numbers and exponents are interval‐valued Pythagorean fuzzy numbers. The prominent characteristic of these proposed operations is studied. Based on these laws, we develop some new weighted aggregation operators, namely the interval‐valued Pythagorean fuzzy weighted exponential averaging operator and the dual interval‐valued Pythagorean fuzzy weighted exponential averaging. Finally, a decision‐making approach is presented based on these operators and illustrated with some numerical examples to validate the developed approach.     

Interval‐valued Pythagorean fuzzy GRA method for multiple‐attribute decision making with incomplete weight information

In this paper, the concept of multiple‐attribute group decision‐making (MAGDM) problems with interval‐valued Pythagorean fuzzy information is developed, in which the attribute values are interval‐valued Pythagorean fuzzy numbers and the information about the attribute weight is incomplete. Since the concept of interval‐valued Pythagorean fuzzy sets is the generalization of interval‐valued intuitionistic fuzzy set. Thus, due the this motivation in this paper, the concept of interval‐valued Pythagorean fuzzy Choquet integral average (IVPFCIA) operator is introduced by generalizing the concept of interval‐valued intuitionistic fuzzy Choquet integral average operator. To illustrate the developed operator, a numerical example is also investigated. Extended the concept of traditional GRA method, a new extension of GRA method based on interval‐valued Pythagorean fuzzy information is introduced. First, utilize IVPFCIA operator to aggregate all the interval‐valued Pythagorean fuzzy decision matrices. Then, an optimization model based on the basic ideal of traditional grey relational analysis (GRA) method is established, to get the weight vector of the attributes. Based on the traditional GRA method, calculation steps for solving interval‐valued Pythagorean fuzzy MAGDM problems with incompletely known weight information are given. The degree of grey relation between every alternative and positive‐ideal solution and negative‐ideal solution is calculated. To determine the ranking order of all alternatives, a relative relational degree is defined by calculating the degree of grey relation to both the positive‐ideal solution and negative ideal solution simultaneously. Finally, to illustrate the developed approach a numerical example is to demonstrate its practicality and effectiveness.     

The cut sets,decomposition theorems and representation theorems on intuitionistic fuzzy sets and interval valued fuzzy sets

In this paper,the cut sets,decomposition theorems and representation theorems of intuitionistic fuzzy sets and interval valued fuzzy sets are researched indail.First,new definitions of four kinds of cut sets on intuitionistic fuzzy sets are introduced,which are generalizations of cut sets on Zadeh fuzzy sets and have the same properties as that of Zadeh fuzzy sets.Second,based on these new cut sets,the decomposition theorems and representation theorems on intuitionistic fuzzy sets are established.Each kind ...     

The linear assignment method for multicriteria group decision making based on interval‐valued Pythagorean fuzzy Bonferroni mean

The interval‐valued Pythagorean fuzzy sets can easily handle uncertain information more flexibly in the process of decision making. Considering the interrelationship among the input arguments, we extend the Bonferroni mean and the geometric Bonferroni mean to the interval‐valued Pythagorean fuzzy environment and solve its practical application problems. First, we develop the interval‐valued Pythagorean fuzzy Bonferroni mean and the weighted interval‐valued Pythagorean fuzzy Bonferroni mean (WIVPFBM) operators. The properties of these aggregation operators are investigated. Then, we also develop the interval‐valued Pythagorean fuzzy geometric Bonferroni mean and the weighted interval‐valued Pythagorean fuzzy geometric Bonferroni mean (WIVPFGBM) operators and analyze their properties. Third, we utilize the WIVPFBM and WIVPFGBM operators to fuse the information in the interval‐valued Pythagorean fuzzy multicriteria group decision making (IVPFMCGDM) problem, which can obtain much more information in the process of group decision making. With the aid of the linear assignment method, we present its extension and further design a new algorithm for the application of IVPFMCGDM. Finally, an example is given to elaborate our proposed algorithm and validate its excellent performance.