因素空间反馈外延包络及其改善

研究了因素空间中概念外延的两种近似方法,即反馈外延外包络和反馈外延内包络。首先从概念及其对立概念出发定义了这两种外延近似,讨论了其与粗糙集的上、下近似的关系,得出它们之间具有一致性的结论,并以此给出了两种包络之间的相关性质。随后,讨论了反馈外延包络对概念外延逼近精度问题,给出了四种改善方法。     

基于因素空间理论的直觉模糊概念外延构建及其在决策中的应用

在因素空间理论基础上,提出直觉模糊概念,从原概念及其对立概念的表现外延出发,构造了直觉模糊概念外延的两种逼近,并在此基础上提出了基于反馈外延双层包络的DFE决策方法,最后,给出操作步骤并通过实例对上述理论方法进行了应用。     

转移下半连续函数的极大极小原理及其应用

本文引入了转移下半连续的概念并在转移下半连续的条件下推了ＫｙＦａｎ极大极小原理。应用这一结果，证明了截口定理，不动点定理和函数不等式组解的存在性定理。     

直觉模糊集的扩展原理

基于文[1]给出的直觉模糊集的截集、分解定理和表现定理,利用模糊集的扩展原理,本文建立了直觉模糊集的扩展原理.首先,给出了直觉模糊集的扩展原理及其等价形式;其次,讨论了直党模糊集的扩展原理的有关性质;最后,研究了复合函数的直觉模糊集扩展原理及其性质.     

基于因素空间理论的犹豫模糊群决策

为了更充分的利用数据信息, 本文提出了以犹豫模糊集作为概念的反馈外延.进而给出了考虑犹豫度的犹豫模糊集间的关系与运算; 基于此运算, 定义了模糊概念的外延包络, 并利用包络来集结多因素的偏好信息, 最后给出群决策步骤, 并通过实例对上述理论方法进行了应用。     

空间的几种超投影性质及其局部化

讨论Banach空间几种超投影性质(及其相应的局部化性质)之间的关系,证明了在Banach空间X自反的条件下,X是l_p-次投影空间的充要条件是X^*是l_p-超投影空间,X是局部l_p-次投影空间的充要条件是X^*是局部l_p-超投影空间,以及X是局部次投影空间的充要条件是X^*是局部超投影的。其中1/p+1/q=1(p>1,q>1)。     

G-凸空间中的择一原理和极大极小不等式

利用Kuo、Jeng和Huang提出的不动点定理,给出G-凸空间中关于3个映射值的非常一般的相交定理.由此结果依次导出了关于极大元、解析择一和极大极小不等式的择一定理.     

Banach空间中φ-渐进非扩展映像不动点的迭代构造

在Mann的迭代算法基础上，运用Banach空间中的广义投影，使渐进非扩展映像每次迭代生成的序列都投影到一个闭凸的集合中．并证明了该算法的强收敛性．     

局部凸空间中集值映射的极小不动点定理及其应用

利用局部凸空间中Fan-Kakutani不动点定理,得到局部凸空间中集值映射的极小不动点定理,应用此定理,证明了半线性不适定的算子方程的最小范数极值解的存在性.此结果可以应用到不适定常微方程的两点边值问题,不适定偏微方程的边值问题.     

Fuzzy数的扩张运算及其性质

本文讨论了Ｆ数的扩张加法和扩张数乘运算的性质；并举反例说明这样的扩张运．算不能使Ｆ数全体Ｆ＊构成线性空间；最后对可列个Ｆ数的运算进行了讨论．     

扩张原理的粗集表示

粗集、模糊集均是处理不确定信息的数据分析工具,是数据挖掘的重要方法.由Zadeh首先提出的模糊扩张原理是模糊集理论的最基本的原理之一,粗集是通过上、下近似算子来发挥作用的.本文讨论扩张原理与粗集上近似之间的关系,证明了扩张原理可以表示成粗集上近似的形式,因此,扩张原理成了粗集与模糊集之间的桥梁.此外,借助粗集上、下近似算子的公理系统解决了扩张原理的反问题.     

基于可拓集合的动态分类及其UML表示方法研究

可拓集合是分析事物的可变性和多变性的理论基础 .本文首先建立了物元与类之间的联系 ,在可拓集合零界的基础上建立了过渡类 ,为了形式化描述出多值分类 ,对关联函数进行约束 ,并利用可拓域与物元变换探讨了动态分类机制 ,最后采用 UML构造型扩展机制对动态分类的表示问题进行初步的研究 .     

Additive Properties of the Dufresne Laws and Their Multivariate Extension

The Dufresne laws are defined on the positive line by their Mellin transform , where the a _i and b _j are positive numbers, with pq, and where (x) _s denotes (x+s)/(x). Typical examples are the laws of products of independent random variables with gamma and beta distributions. They occur as the stationary distribution of certain Markov chains (X _n) on defined by where X ₀, (A ₁, B ₁),..., (A _n, B _n),... are independent. This paper gives some explicit examples of such Markov chains. One of them is surprisingly related to the golden number. While the properties of the product of two independent Dufresne random variables are trivial, we give several properties of their sum: the hypergeometric functions are the main tool here. The paper ends with an extension of these Dufresne laws to the space of positive definite matrices and to symmetric cones.     

Generalized Extension Principle

The conventional extension principle was established on the Euclidean space and defined by considering the minimum or t-norm operator. The generalized extension principle proposed in this paper is established on the Hausdorff space and defined by considering an operator that is more general than the t-norm operator. On the other hand, based on the topological structure, we also discuss the properties of 0-level sets by considering the closure. Many interesting and useful equalities considering the 0-level sets will be obtained in this paper.     

An n-Dimensional Hahn-Banach Extension Theorem and Minimal Projections

Let T~=_i=1 ⁿ _irv_i:V V=[v₁,. . . .,v_n] X, where _i V* and X is a Banach space. Let T= _i=1 ⁿu_iv_i: X V be an extension of T~ to all of X (i.e., u_i X*) such that T has minimal (operator) norm. (E.g., if T~=I, T is a minimal projection from X onto V.) Then it is necessary and sufficient that u:=u_1,. . . ,u_n is given by (v:=v₁,. . . ,v_n)ext_v(u) Vⁿ,where the notion of a v-extremal (ext_v) of u is properly defined.The condition above leads in many important cases to a simple geometric interpretation of minimal projections. Furthermore, by applying this formula to the case X=L^p, we obtain a linear n-dimensional analog of the Hölder equality condition (M is given by ext_v(u)=Mv)1/p u · Mv = 1/q u · Mv,wherever v is differentiable.We point out several applications, including the determination of the absolute projection constant of _n ^p      

Weierstrass Representation of Some Simply-Periodic Minimal Surfaces

We prove a desingularization result for minimal surfaces inEuclidean space using Weierstrass representation. We solve the periodproblem using the implicit function theorem at a degenerate point.     

Optimal Properties of Orthogonal Arrays Based on ANOVA High-Dimensional Model Representation

Global sensitivity indices play importantroles in global sensitivity analysis based on ANOVA high-dimensionalrepresentation, Wang et al. (2012) showed that orthogonal arraysare A-optimality designs for the estimation of parameter ,the definition of which can be seen in Section 2. This paperpresented several other optimal properties of orthogonal arraysunder ANOVA high-dimensional representation, including E-optimalityfor the estimation of  and universal optimality for theestimation of , where  is the independentparameters of . Simulation study showed that randomizedorthogonal arrays have less biased and more precise in estimatingthe confidence intervals comparing with other methods.     

Every Commutative Ring Has a Minimal Ring Extension

Let R be a commutative unital ring and E a unital R-module. Then the canonical injective ring homomorphism from R into the idealization R(+) E is a minimal ring homomorphism if and only if E is a simple R-module. For E nonzero, R(+)E is not (R-algebra isomorphic to) an overring of R. If E ₁ and E ₂ are nonisomorphic simple R-modules, then R(+) E ₁ and R(+) E ₂ give minimal ring extensions of R which are not isomorphic as R-algebras. The ring of dual numbers over R is a minimal ring extension of R ? R × R is a minimal ring extension of R ? R is a field.