拓扑空间关于子基的紧致性

覆盖方法的应用在粗糙集理论研究中越来越受到重视,其中拓扑空间的子集关于子基的内部和闭包两个概念尤为重要.在由它们导入的关于子基的开集,闭集的基础上,给出了拓扑空间关于子基的紧致性概念,并研究它的性质,得到一般拓扑空间中紧致性的一种推广.     

拓扑空间关于子基的分离性

在粗糙集理论研究中,覆盖方法的应用越来越受到重视,其中拓扑空间的子集关于子基的内部和闭包两个概念尤为重要.本文在由它们导人的关于子基的开集,闭集的基础上,给出了拓扑空间关于子基的分离性概念,并研究它们的性质,得到分离性公理定义的一般拓扑空间的进一步分类.     

关于子基的连通性的注记

在粗糙集理论研究中,覆盖方法的应用越来越受重视,其中最重要的概念是最近引进的拓扑空间的子集关于子基的内部和闭包以及由它们导入的关于子基的开集、闭集.对由它们导入的拓扑空间关于子基的隔离子集、连通性作进一步研究,所得性质是一般拓扑空间中隔离子集和连通性相应结果的推广.     

关于子基的连通性

覆盖方法在粗糙集理论研究中的应用越来越受到重视,而其中最重要的两个概念是最近引入的拓扑空间的子集关于子基的内部和闭包.本文研究由它们导出的关于子基的连通性的概念,它比一般拓扑学中的连通性的概念弱,但具有许多类似的性质,这些性质事实上也是连通性相应结果的推广.     

近似空间的拓扑性质及其应用

近似空间(U,R)的全体可定义集构成X上的一个拓扑.本文在不要求论域U是有限的前提下探讨近似空间上这个拓扑的局部性质和可数性质,以及拓扑空间可近似化的充要条件及公理化体系,并寻找它们在粗糙集理论中的应用.     

关于子基的局部连通性

在粗燥集理论研究中,覆盖方法的应用越来越受到重视,其中拓扑空间的子集关于子基的内部和闭包两个概念尤为重要.在最近由它们导入的关于子基的连通性基础上,给出了关于子基的局部连通性概念,并研究它的性质,得到一般拓扑学中局部连通性的一种推广.     

粗糙集理论在伪BCK代数上的应用

本文把粗糙集理论应用到伪BCK代数, 作为伪BCK代数的推广, 给出了类代数近似空间上粗伪BCK代数、粗子代数和粗伪滤子的概念, 并讨论了它们的一些相关性质. 进一步研究了伪BCK 代数近似空间上粗子代数和粗伪滤子. 最后给出了几个伪BCK代数、伪滤子和子代数的验证程序.     

近似空间与信任结构之间的关系

回顾了由二元关系产生的粗糙近似空间及其导出的各种粗糙近似算子的构造性定义,介绍了经典和模糊环境下各种信任结构及其导出的信任函数与似然函数的概念,给出了粗糙集理论中近似空间及其导出的下近似算子与上近似算子和证据理论中的信任结构及其导出信任函数与似然函数之间的相互关系及其应用背景。     

覆盖空间及粗糙集与拓扑的统一

引入覆盖空间,定义了其邻域、内部、闭包、测度等概念,研究了它们的性质.得出了粗糙集近似空间和拓扑空间都是具体覆盖空间的重要结论,从而用覆盖空间统一了粗糙集和拓扑.利用覆盖空间,得到了粗糙集和拓扑中更深刻的性质,从算子论和集合论的角度丰富和深化了粗糙集与拓扑的内容.     

决策信息系统中的拓扑学方法

在决策信息系统中引入拓扑结构,借助拓扑学的基本概念(拓扑、内部和闭包等)研究决策问题,用它们刻画决策信息系统中的一些重要概念(决策协调集、决策约简集、下近似协调集、下近似约简集、上近似协调集、上近似约简集),并利用它们把这些重要概念推广到最一般的情况,建立起相应的约简理论.     

On some types of covering rough sets from topological points of view

The concept of coverings is one of the fundamental concepts in topological spaces and plays a big part in the study of topological problems. This motivates the research of covering rough sets from topological points of view. From topological points of view, we can get a good insight into the essence of covering rough sets and make our discussions concise and profound. In this paper, we first construct a type of topology called the topology induced by the covering on a covering approximation space. This notion is indeed in the core of this paper. Then we use it to define the concepts of neighborhoods, closures, connected spaces, and components. Drawing on these concepts, we define several pairs of approximation operators. We not only investigate the relationships among them, but also give clear explanations of the concepts discussed in this paper. For a given covering approximation space, we can use the topology induced by the covering to investigate the topological properties of the space such as separation, connectedness, etc. Finally, a diagram is presented to show that the collection of all the lower and upper approximations considered in this paper constructs a lattice in terms of the inclusion relation ⊆.     

基于覆盖上近似算子的拟阵结构及其关系

Covering-based rough sets,as a technique of granular computing,can be a useful tool for dealing with inexact,uncertain or vague knowledge in information systems.Matroids generalize linear independence in vector spaces,graph theory and provide well established platforms for greedy algorithm design.In this paper,we construct three types of matroidal structures of covering-based rough sets.Moreover,through these three types of matroids,we study the relationships among these matroids induced by six types of covering-based upper approximation operators.First,we construct three families of sets by indiscernible neighborhoods,neighborhoods and close friends,respectively.Moreover,we prove that they satisfy independent set axioms of matroids.In this way,three types of matroidal structures of covering-based rough sets are constructed.Secondly,we study some characteristics of the three types of matroid,such as dependent sets,circuits,rank function and closure.Finally,by comparing independent sets,we study relationships among these matroids induced by six types of covering-based upper approximation operators.     

Matroidal approaches to rough sets via closure operators

This paper studies rough sets from the operator-oriented view by matroidal approaches. We firstly investigate some kinds of closure operators and conclude that the Pawlak upper approximation operator is just a topological and matroidal closure operator. Then we characterize the Pawlak upper approximation operator in terms of the closure operator in Pawlak matroids, which are first defined in this paper, and are generalized to fundamental matroids when partitions are generalized to coverings. A new covering-based rough set model is then proposed based on fundamental matroids and properties of this model are studied. Lastly, we refer to the abstract approximation space, whose original definition is modified to get a one-to-one correspondence between closure systems (operators) and concrete models of abstract approximation spaces. We finally examine the relations of four kinds of abstract approximation spaces, which correspond exactly to the relations of closure systems.     

广义近似空间的粗糙同胚与拓扑同胚

对广义近似空间之间的映射引入并刻画了粗糙连续性和拓扑连续性,探讨了他们的性质及相互关系.证明了两个粗糙连续映射的复合还是粗糙连续的,每个粗糙连续的映射都是拓扑连续的.在此基础上引入了粗糙同胚性质和拓扑同胚性质的概念,证明了拓扑同胚性质均为粗糙同胚性质并考察了广义近似空间的诸如分离性、连通性、紧性等的粗糙同胚不变性和拓扑同胚不变性.     

F格上的逼近算子

粗集理论是波兰学者Pawlak提出的知识表示新理论.Pawlak代数是粗集理论中粗集系统的抽象,其公理系统包含了知识粗表示所必须的全部性质.本文深入研究了F格上的逼近算子,建立了F格上弱逼近算子之间的某些代数运算,从而从理论上建立了各种知识粗表示之间的联系.我们还定义了逼近算子的闭包,进而用逼近算子导出拓扑,为信息系统的近似提供必要的数学基础.最后,作为特例,我们研究了粗集理论中由相似关系导出逼近算子的某些性质.     

算子概率范数与共鸣定理

提出概率赋范线性空间上集合有界性的简化定义,利用算子概率范数概念·进一步研究概率赋范线性空间上的线性算子理论,并在算子概率赋范空间上,建立了概率有界、概率半有界、非概率无界意义下的共鸣定理·     

有关拓扑学与覆盖粗糙集的一些结论

引入了拓扑覆盖的概念,并结合最小描述元对有限论域上的拓扑覆盖加于研究,得出了拓扑覆盖的最简覆盖和基与最小描述元之间的关系.介绍了在基于有限论域U上的覆盖,构造U上的一个拓扑的方法.并且在最小描述元的基础上将划分下的粗糙隶属函数推广至一般覆盖下的粗糙隶属函数,而后介绍了其相关运用.     

程度下近似算子与变精度上近似算子的差运算模型

目的是探讨精度与程度的复合,建立并研究新的粗糙集拓展模型.基于程度与精度的逻辑差需求,提出了程度下近似算子与变精度上近似算子的差运算模型,得到了程度下近似算子与变精度上近似算子的差运算的宏观本质、精确描述与基本性质.并用一个医疗实例说明了模型的意义和应用.程度下近似算子与变精度上近似算子的差运算模型,部分的拓展了程度粗糙集模型和经典粗糙集模型.     

Covering rough sets based on neighborhoods: An approach without using neighborhoods

Rough set theory, a mathematical tool to deal with inexact or uncertain knowledge in information systems, has originally described the indiscernibility of elements by equivalence relations. Covering rough sets are a natural extension of classical rough sets by relaxing the partitions arising from equivalence relations to coverings. Recently, some topological concepts such as neighborhood have been applied to covering rough sets. In this paper, we further investigate the covering rough sets based on neighborhoods by approximation operations. We show that the upper approximation based on neighborhoods can be defined equivalently without using neighborhoods. To analyze the coverings themselves, we introduce unary and composition operations on coverings. A notion of homomorphism is provided to relate two covering approximation spaces. We also examine the properties of approximations preserved by the operations and homomorphisms, respectively.