On Three Types of Covering-Based Rough Sets

Rough set theory is a useful tool for data mining. It is based on equivalence relations and has been extended to covering-based generalized rough set. This paper studies three kinds of covering generalized rough sets for dealing with the vagueness and granularity in information systems. First, we examine the properties of approximation operations generated by a covering in comparison with those of the Pawlak's rough sets. Then, we propose concepts and conditions for two coverings to generate an identical lower approximation operation and an identical upper approximation operation. After the discussion on the interdependency of covering lower and upper approximation operations, we address the axiomization issue of covering lower and upper approximation operations. In addition, we study the relationships between the covering lower approximation and the interior operator and also the relationships between the covering upper approximation and the closure operator. Finally, this paper explores the relationships among these three types of covering rough sets.     

区间值Fuzzy集分解定理上的近似算子研究

将广义粗糙模糊下、上近似算子拓展到区间上,并利用区间值模糊集分解定理给出一组新的广义区间值粗糙模糊下、上近似算子,证明二者在由任意二元经典关系构成的广义近似空间中是等价的,最后讨论了在一般二元关系下,两组近似算子的性质。     

An axiomatic characterization of a fuzzy generalization of rough sets

In rough set theory, the lower and upper approximation operators defined by a fixed binary relation satisfy many interesting properties. Several authors have proposed various fuzzy generalizations of rough approximations. In this paper, we introduce the definitions for generalized fuzzy lower and upper approximation operators determined by a residual implication. Then we find the assumptions which permit a given fuzzy set-theoretic operator to represent a upper (or lower) approximation derived from a special fuzzy relation. Different classes of fuzzy rough set algebras are obtained from different types of fuzzy relations. And different sets of axioms of fuzzy set-theoretic operator guarantee the existence of different types of fuzzy relations which produce the same operator. Finally, we study the composition of two approximation spaces. It is proved that the approximation operators in the composition space are just the composition of the approximation operators in the two fuzzy approximation spaces.     

Topological approaches to covering rough sets

Rough sets, a tool for data mining, deal with the vagueness and granularity in information systems. This paper studies covering-based rough sets from the topological view. We explore the topological properties of this type of rough sets, study the interdependency between the lower and the upper approximation operations, and establish the conditions under which two coverings generate the same lower approximation operation and the same upper approximation operation. Lastly, axiomatic systems for the lower approximation operation and the upper approximation operation are constructed.     

New topological approach of rough set generalizations

In this paper, we introduce a generalization of rough set theory using topological structures generated by any binary general relation. The class of all after-composed sets and the class of all fore-composed sets defined here are used to generate two topological spaces. These topologies are used to approximate sets topologically. Lower and upper approximations are defined topologically and some of their properties are studied using these topologies. Also, membership, equality, inclusion relations and power set notions in the generalized approximation space are studied. Many differences are shown between notions of ordinary set theory and notions of rough set theory. These notions introduced in this work are good future work to knowledge discovery and data mining.     

双论域粗糙集的矩阵表示

在双论域粗糙集中,不论是理论上还是应用上,矩阵方法都是一种简单且高效的计算方法。利用矩阵的方法来研究双论域粗糙集。提出了双论域上的关系矩阵,通过关系矩阵以及关系矩阵的转置,构造了两个布尔方阵。利用这两个布尔方阵的特征研究了双论域覆盖粗糙集的一些性质。定义了一种布尔矩阵之间新的运算,并且利用这个运算,简洁地表示了双论域覆盖粗糙集的上近似算子和关系粗糙集的下近似算子。     

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.     

双论域上的广义直觉模糊概率粗糙集模型及其应用

已有的双论域直觉模糊概率粗糙集模型通过设置两个阈值${\lambda _1}$、${\lambda _2} $,讨论了经典集合在直觉模糊二元关系下的概率粗糙下上近似。该模型不能计算直觉模糊集合在直觉模糊二元关系下的概率粗糙下上近似,这在一定程度上限制了该模型的应用。首先给出了直觉模糊条件概率的定义。在直觉模糊概率空间下构造了双论域广义直觉模糊概率粗糙集模型,讨论了模型的主要性质。最后,将模型应用到临床诊断系统中。与其他模型相比,所提出的广义直觉模糊概率粗糙集模型进一步丰富了概率粗糙集理论,更适合于实际应用。     

变精度覆盖粗糙集模型的比较

介绍覆盖粗糙集和Ziarko变精度粗糙集模型,将Ziarko变精度粗糙近似算子应用于覆盖近似空间,借助引入的误差参数β (0 ≤β<0.5),给出2种变精度覆盖粗糙集模型的β上近似、β下近似、β边界和β负域的定义。讨论2种模型中β上、下近似算子的基本性质、2种模型之间的关系以及变精度覆盖粗糙集模型与其他粗糙集模型的关系。     

积模糊粗集模型及其模糊知识粒的表示和分解

为处理人工智能中不精确和不确定的数据和知识,Pawlak提出了粗集理论。之后粗集理论被推广,其方法主要有二:一是减弱对等价关系的依赖;二是把研究问题的论域从一个拓展到多个。结合这两种思想,研究基于两个模糊近似空间的积模糊粗集模型及其模糊粗糙集的表示和分解。根据这种思想,可以从论域分解的角度探索降低高维模糊粗糙集计算的复杂度问题。先对模糊近似空间的分层递阶结构———λ-截近似空间进行研究,得到不同层次知识粒的相互关系;然后定义模糊等价关系的积,并研究其性质及算法;最后构建基于积模糊等价关系的积模糊粗集模型,并讨论了该模型中模糊粗糙集的表示及分解问题,分别从λ-截近似空间和一维模糊近似空间的角度去处理,给出了可分解集的上(下)近似的一个刻画,及模糊可分解集的上(下)近似的λ-截集分解算法。     

邻域系统粗糙集和覆盖粗糙集

邻域系统粗糙集和覆盖粗糙集是经典粗糙集的两种重要扩展。通过分别比较各模型中下(上)近似集之间的包含关系和近似精度之间的大小关系,深入探讨邻域系统粗糙集和6种覆盖粗糙集模型之间的关系,得出了邻域系统粗糙集和6种覆盖粗糙集模型的下(或上)近似集之间的关系是明确的,其要么是可以比较的,要么是不可以比较的,证明了可比较的具有包含甚至等价关系,不可比较的通过反例进行了佐证。对不同扩展粗糙集的对比研究加深了对这些模型的理解,同时也为宏观上学习和认识粗糙集提供了帮助。     

广义区间值模糊粗糙近似算子的构造研究

构造了一组新的广义模糊粗糙近似算子,将其拓展到区间上.在由任意的二元区间值模糊关系构成的广义近似空间中,证明了该组近似算子与区间化的广义Dubois模糊粗糙近似算子是等价的,最后在一般二元区间值模糊关系下对该组近似算子的性质进行了讨论.     

Rough fuzzy approximations on two universes of discourse

In rough set theory, the lower and upper approximation operators can be constructed via a variety of approaches. Various fuzzy generalizations of rough approximation operators have been made over the years. This paper presents a framework for the study of rough fuzzy sets on two universes of discourse. By means of a binary relation between two universes of discourse, a covering and three relations are induced to a single universe of discourse. Based on the induced notions, four pairs of rough fuzzy approximation operators are proposed. These models guarantee that the approximating sets and the approximated sets are on the same universes of discourse. Furthermore, the relationship between the new approximation operators and the existing rough fuzzy approximation operators on two universes of discourse are scrutinized, and some interesting properties are investigated. Finally, the connections of these approximation operators are made, and conditions under which some of these approximation operators are equivalent are obtained.     

广义粗糙近似算子的拓扑性质

粗糙集理论是一种处理不确定性问题的数学工具.粗糙近似算子是粗糙集理论中的核心概念,基于等价关系的Paw-lak粗糙近似算子可以推广为基于一般二元关系的广义粗糙近似算子.近似算子的拓扑结构是粗糙集理论的重点研究方向.文中主要研究基于一般二元关系的广义粗糙近似算子诱导拓扑的性质,给出了基于粒和基于子系统的广义粗糙近似算子诱...     

粗糙模糊集的构造与公理化方法

用构造性方法和公理化研究了粗糙模糊集．由一个一般的二元经典关系出发构造性地定义了一对对偶的粗糙模糊近似算子,讨论了粗糙模糊近似算子的性质,并且由各种类型的二元关系通过构造得到了各种类型的粗糙模糊集代数．在公理化方法中,用公理形式定义了粗糙模糊近似算子,各种类型的粗糙模糊集代数可以被各种不同的公理集所刻画．阐明了近似算子的公理集可以保证找到相应的二元经典关系,使得由关系通过构造性方法定义的粗糙模糊近似算子恰好就是用公理化定义的近似算子。     

类对称关系下的广义粗糙集模型

针对等价关系下的经典粗糙集,定义弱对称与局部强对称二元关系,构造相应的广义粗糙集模型。给出这2种模型的公理化特征,并将两者结合,得到强对称二元关系下的广义粗糙集模型。理论分析证明,论域上任何集合均为广义精确集的充要条件是其二元关系为强对称关系,即可以利用该模型刻画经典粗糙集中的广义精确集。     

Algorithm and axiomatization of rough fuzzy sets based finite dimensional fuzzy vectors

Rough sets, proposed by Pawlak and rough fuzzy sets proposed by Dubois and Prade were expressed with the different computing formulas that were more complex and not conducive to computer operations. In this paper, we use the composition of a fuzzy matrix and fuzzy vectors in a given non-empty finite universal, constitute an algebraic system composed of finite dimensional fuzzy vectors and discuss some properties of the algebraic system about a basis and operations. We give an effective calculation representation of rough fuzzy sets by the inner and outer products that unify computing of rough sets and rough fuzzy sets with a formula. The basis of the algebraic system play a key role in this paper. We give some essential properties of the lower and upper approximation operators generated by reflexive, symmetric, and transitive fuzzy relations. The reflexive, symmetric, and transitive fuzzy relations are characterized by the basis of the algebraic system. A set of axioms, as the axiomatic approach, has been constructed to characterize the upper approximation of fuzzy sets on the basis of the algebraic system.     

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.     

变精度粗糙集模型及其应用研究

介绍了广义粗糙集模型和Ziarko变精度粗糙集模型,找出了它们的不足;借助引入的误差参数β(0≤β<0.5),给出了基于后继邻域的一般二元关系下变精度粗糙集模型的β上近似、β下近似、3边界和β负域的定义以及β近似质量和β粗糙性测度定义;详细讨论了β上、下近似算子的性质、该模型与其他粗糙集模型的关系以及一般二元关系下两种变精度粗糙集模型的关系;最后,举例说明了该模型在信息处理中的应用。