基于覆盖的直觉模糊粗糙集

通过直觉模糊覆盖概念将覆盖粗糙集模型进行推广,提出一种基于直觉模糊覆盖的直觉模糊粗糙集模型.首先,介绍了直觉模糊集、直觉模糊覆盖和直觉模糊逻辑算子等概念;然后,利用直觉模糊三角模和直觉模糊蕴涵,构建两对基于直觉模糊覆盖的下直觉模糊粗糙近似算子和上直觉模糊粗糙近似算子;最后,给出了这些算子的基本性质并研究了它们之间的对偶性.     

基于蕴涵的区间值直觉模糊粗糙集

提出一种基于区间值直觉模糊蕴涵的区间值直觉模糊粗糙集模型.首先,介绍了区间值直觉模糊集、区间值直觉模糊关系和区间值直觉模糊逻辑算子的概念;然后,利用区间值直觉模糊三角模和区间值直觉模糊蕴涵,在区间值直觉模糊近似空间中定义了区间值直觉模糊集的上近似和下近似;最后,给出并证明了这些近似算子的一些性质.     

直觉模糊三角模的剩余蕴涵及其性质

研究了直觉模糊三角模的剩余蕴涵及其性质。首先,定义了直觉模糊三角模的剩余蕴涵;其次,推导了直觉模糊三角模的剩余蕴涵与三角模的剩余蕴涵的关系;最后,证明了直觉模糊三角模的剩余蕴涵的16条性质。直觉模糊三角模的剩余蕴涵及其性质在直觉模糊推理、群决策等领域具有广阔的应用前景。     

直觉模糊S-粗集时态逻辑算子及扩展运算性质

首先给出直觉模糊S-粗集的基本概念,在直觉模糊S-粗集基本运算的基础上,引入两个典型的作用于直觉模糊S-粗集的时态逻辑算子"□(always)"和"◇(sometimes)",重点研究了直觉模糊S-粗集在时态逻辑算子作用下的若干扩展运算及其性质.最后将这些性质归结为定理,并给出详细的证明过程.     

(I,J)-区间直觉模糊粗糙集

利用吴伟志所定义的两个直觉模糊蕴涵算子I和J,把(I,J)-直觉模糊粗糙集的概念推广到区间直觉模糊集的情形,给出了区间直觉模糊近似空间的概念及(I,J)-区间直觉模糊粗糙集,研究了(I,J)-区间直觉模糊粗糙集的基本性质并推广了张植明等人提出的结论。     

基于遗传算法和隐马尔可夫模型的Web信息抽取的改进

直觉模糊蕴涵是直觉模糊推理的重要基础,为直觉模糊集在不确定信息系统下推理和决策中的应用提供了理论基础。对直觉模糊蕴涵进行了研究。首先回顾了直觉模糊的有关基础知识,在此基础上构造了一种新的广义的直觉模糊蕴涵,证明了其单调性、边界性等系列重要性质,最后证明了该蕴涵可构成直觉模糊剩余格。     

基于T模剩余蕴涵算子的直觉模糊粗糙集

构造并系统研究了直觉模糊T模的剩余蕴涵。在此基础上,推导出了直觉模糊粗糙集的一种构造模型,证明了Pawlak粗糙集、直觉模糊集、模糊粗糙集、粗糙模糊集及模糊T粗糙集都是直觉模糊粗糙集的特殊情形。最后给出并证明了直觉模糊粗糙集的一些性质。     

基于直觉模糊三角模的直觉模糊粗糙集

提出一种基于直觉模糊三角模的直觉模糊粗糙集.首先,定义了直觉模糊集上的T模及其剩余蕴涵,研究了直觉模糊T模的剩余蕴涵的性质,并推导了通用计算表达式;然后,将模糊T粗糙集扩展成直觉模糊粗糙集,证明了模糊T粗糙集、粗糙模糊集和Pawlak粗糙集都是直觉模糊粗糙集的特殊情形;最后,证明了直觉模糊粗糙集的一些性质.     

直觉模糊逻辑的语义算子研究

首先引用Atanassov直觉模糊集的基本概念和运算。在阐明直觉模糊集的集中、扩张、归一化算子之后，新定义了强化算子。通过考察Atanassov直觉模糊集与Zadeh模糊集之间的关系，给出了直觉模糊语言、结构化直觉模糊语言和直觉模糊语义的数学描述，重点对基于直觉模糊集和直觉模糊关系的模糊语言的语义算子，如语气算子、模糊化算子、判定化算子及连接与否定算子等进行了研究，并举例阐明其应用，使直觉模糊逻辑的语义算子得到进一步的拓广。     

三角模糊数直觉模糊Bonferroni平均算子及其应用

针对决策信息为三角模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出了一种基于三角模糊数直觉模糊加权Bonferroni平均(TFNIFWBM)算子的决策方法。首先,基于TFNIFN的运算法则和Bonferroni平均(BM)算子,定义了三角模糊数直觉模糊BM算子和TFNIFWBM算子;然后,研究了这些算子的一些性质,建立基于TFNIFWBM算子的MAGDM模型,结合排序方法进行决策。最后通过MAGDM算例验证了该算子的有效性与可行性。     

On characterization of intuitionistic fuzzy rough sets based on intuitionistic fuzzy implicators

This paper presents a general framework for the study of relation-based (I,T)-intuitionistic fuzzy rough sets by using constructive and axiomatic approaches. In the constructive approach, by employing an intuitionistic fuzzy implicator I and an intuitionistic fuzzy triangle norm T, lower and upper approximations of intuitionistic fuzzy sets with respect to an intuitionistic fuzzy approximation space are first defined. Properties of (I,T)-intuitionistic fuzzy rough approximation operators are examined. The connections between special types of intuitionistic fuzzy relations and properties of intuitionistic fuzzy approximation operators are established. In the axiomatic approach, an operator-oriented characterization of (I,T)-intuitionistic fuzzy rough sets is proposed. Different axiom sets characterizing the essential properties of intuitionistic fuzzy approximation operators associated with various intuitionistic fuzzy relations are explored.     

On generalized intuitionistic fuzzy rough approximation operators

In rough set theory, the lower and upper approximation operators defined by binary relations satisfy many interesting properties. Various generalizations of Pawlak’s rough approximations have been made in the literature over the years. This paper proposes a general framework for the study of relation-based intuitionistic fuzzy rough approximation operators within which both constructive and axiomatic approaches are used. In the constructive approach, a pair of lower and upper intuitionistic fuzzy rough approximation operators induced from an arbitrary intuitionistic fuzzy relation are defined. Basic properties of the intuitionistic fuzzy rough approximation operators are then examined. By introducing cut sets of intuitionistic fuzzy sets, classical representations of intuitionistic fuzzy rough approximation operators are presented. The connections between special intuitionistic fuzzy relations and intuitionistic fuzzy rough approximation operators are further established. Finally, an operator-oriented characterization of intuitionistic fuzzy rough sets is proposed, that is, intuitionistic fuzzy rough approximation operators are defined by axioms. Different axiom sets of lower and upper intuitionistic fuzzy set-theoretic operators guarantee the existence of different types of intuitionistic fuzzy relations which produce the same operators.     

Some geometric aggregation operators based on intuitionistic fuzzy sets

The weighted geometric (WG) operator and the ordered weighted geometric (OWG) operator are two common aggregation operators in the field of information fusion. But these two aggregation operators are usually used in situations where the given arguments are expressed as crisp numbers or linguistic values. In this paper, we develop some new geometric aggregation operators, such as the intuitionistic fuzzy weighted geometric (IFWG) operator, the intuitionistic fuzzy ordered weighted geometric (IFOWG) operator, and the intuitionistic fuzzy hybrid geometric (IFHG) operator, which extend the WG and OWG operators to accommodate the environment in which the given arguments are intuitionistic fuzzy sets which are characterized by a membership function and a non-membership function. Some numerical examples are given to illustrate the developed operators. Finally, we give an application of the IFHG operator to multiple attribute decision making based on intuitionistic fuzzy sets.     

Choquet integrals of weighted intuitionistic fuzzy information

The Choquet integral is a very useful way of measuring the expected utility of an uncertain event [G. Choquet, Theory of capacities, Annales de l’institut Fourier 5 (1953) 131-295]. In this paper, we use the Choquet integral to propose some intuitionistic fuzzy aggregation operators. The operators not only consider the importance of the elements or their ordered positions, but also can reflect the correlations among the elements or their ordered positions. It is worth pointing out that most of the existing intuitionistic fuzzy aggregation operators are special cases of our operators. Moreover, we propose the interval-valued intuitionistic fuzzy correlated averaging operator and the interval-valued intuitionistic fuzzy correlated geometric operator to aggregate interval-valued intuitionistic fuzzy information, and apply them to a practical decision-making problem involving the prioritization of information technology improvement projects.     

Generalized intuitionistic fuzzy geometric interaction operators and their application to decision making

Considering that there may exist some interactions between membership function and non-membership function of different intuitionistic fuzzy sets, we present some new operational laws from the probability point of view and give a geometric interpretation of the new operations. Based on which, a new class of generalized intuitionistic fuzzy aggregation operators are developed, including the generalized intuitionistic fuzzy weighted geometric interaction averaging (GIFWGIA) operator, the generalized intuitionistic fuzzy ordered weighted geometric interaction averaging (GIFOWGIA) operator and the generalized intuitionistic fuzzy hybrid geometric interaction averaging (GIFHGIA) operator. The properties of these new generalized aggregation operators are investigated. Moreover, approaches to multiple attributes decision making are given based on the generalized aggregation operators under intuitionistic fuzzy environment, and an example is illustrated to show the validity and feasibility of new approach. Finally, we give a systematic comparison between the work of this paper and that of other papers.     

Intuitionistic fuzzy recognizers and intuitionistic fuzzy finite automata

Intuitionistic fuzzy recognizers and intuitionistic fuzzy finite automata are discussed. The notions of intuitionistic fuzzy recognizer, complete accessible intuitionistic fuzzy recognizer, intuitionistic fuzzy finite automata, deterministic intuitionistic fuzzy finite automata, and intuitionistic fuzzy language are introduced. It is shown that the languages recognized by intuitionistic fuzzy recognizer are regular, and the intuitionistic fuzzy languages recognized by the intuitionistic fuzzy finite automaton and the intuitionistic fuzzy languages recognized by deterministic intuitionistic fuzzy finite automaton are equivalent. This work is supported by National Science Foundation of China (Grant No.10571112), “TRAPOYT” of China and National 973 Foundation Research Program(Grant No.2002CB312200).     

Characterization of rough set approximations in Atanassov intuitionistic fuzzy set theory

The primitive notions in rough set theory are lower and upper approximation operators defined by a fixed binary relation and satisfying many interesting properties. Many types of generalized rough set models have been proposed in the literature. This paper discusses the rough approximations of Atanassov intuitionistic fuzzy sets in crisp and fuzzy approximation spaces in which both constructive and axiomatic approaches are used. In the constructive approach, concepts of rough intuitionistic fuzzy sets and intuitionistic fuzzy rough sets are defined, properties of rough intuitionistic fuzzy approximation operators and intuitionistic fuzzy rough approximation operators are examined. Different classes of rough intuitionistic fuzzy set algebras and intuitionistic fuzzy rough set algebras are obtained from different types of fuzzy relations. In the axiomatic approach, an operator-oriented characterization of rough sets is proposed, that is, rough intuitionistic fuzzy approximation operators and intuitionistic fuzzy rough approximation operators are defined by axioms. Different axiom sets of upper and lower intuitionistic fuzzy set-theoretic operators guarantee the existence of different types of crisp/fuzzy relations which produce the same operators.     

广义的直觉模糊蕴涵及剩余格

根据交通流的动态变化情况,实时优化交通信号配时,是减少交通延误,提高交通效率的有效方法。为减少信号优化时间,提高时效性,提出一种并行化的交通信号对比分析算法,该算法首先根据专家经验和交通管理常识设定一定的信号变化区间,然后针对该区间给定变化区间Δ,依次给定相应的信号配时策略,将每一种信号配时策略分配给集群系统中的一个计算节点,由各个计算节点分别进行仿真运算,最后由主节点聚合分析,对比给出最优信号控制方案。以微观交通仿真系统Paramics进行了仿真实验,结果表明,在4个节点组成的并行网络中,加速比为1.75,其提高了仿真效率,且能较好地遴选出最优控制方案。