Fuzzy network technique for technological forecasting

The stochastic network technique is known to be a powerful tool carrying out a technological forecast of complex systems. A network dealt with is characterized by a tetrad of essential elements: logical nodes with some inputs and outputs, probabilistics activity branches, feedback loops, and multiple sources and sinks. A set of network parameters is defined for each element and their values are estimated for practical analysis of the network. In the case where the system to be treated is very large and/or complex, it cannot always be represented by a definite network and therefore forecasted values of parameters are inevitably indefinite themselves. A conventional probabilistic approach is sometimes inadequate in such a case. In the light of these facts, the paper proposes a fuzzy network technique, in which among activity branches emanating from a node, a branch to be undertaken once the node is realized belongs to a fuzzy set; and the time required to complete an activity branch belongs to a fuzzy set. Operations of maximum and minimum for sum and product of fuzzy sets take the place of manipulations of addition and multiplication for probabilities, respectively. Although the operations are somewhat formal, the obtained results seem interesting. A numerical example is attached to show a comparison of the proposed technique with the conventional one.     

Fuzzy同余和正规Fuzzy子群(英文)

自从A. Rosenfeld在1971年提出Fuzzy子群的概念以来,在Fuzzy群的研究方面已有不少进展,例如见[1,2,5,6,10,11,14]。另一方面,L.A.Zadeh首创的Fuzzy关系理论的研究也是硕果累累,例如见[3,4,8,12,13,15]。本文通过Fuzzy同余关系和正规Fuzzy子群的相互联系,将这两个方向的研究成果进行“嫁接”和“杂交”,得到许多有趣的结果。主要结果是定理2.7,定理3.1和3.6。本文另一主题是引入T-Fuzzy群的正规T-Fuzzy子群的新概念,当T是正则t-范算子时,得到了T-Fuzzy群的三个同构定理,作者认为它比现有的相应同构定理更为简洁、广泛和自然。     

一类特殊的Fuzzy局部凸空间

文中给出了Ｆｕｚｙ有界型空间的定义，在此基础上，讨论了Ｆｕｚｙ有界型空间的等价定理，最后证明了Ｑ－Ｃ_ＩＦｕｚｙ局部凸空间是有界型的．     

机械结构的模糊优化设计

本文阐述了机械结构模糊优化设计的必要性及方法，并以用于５５千瓦风力发电机组的ＮＧＷ９２型行星齿轮传动为例，说明这一现代设计方法的实施及优良设计特性。     

The Equivalence of the DFA and OFA Automate

ＴｈｅＥｑｕｉｖａｌｅｎｃｅ　ｏｆｔｈｅＰＦＡａｎｄＯＦＡＡｕｔｏｍａｔａＴｈｅＥｑｕｉｖａｌｅｎｃｅｏｆｔｈｅＰＦＡａｎｄＯＦＡＡｕｔｏｍａｔａ￥／／ＬｉＧｕｏｃａｉａｎｄＷａｎｇＣｈｕａｎｈｏｎｇ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，...     

定义在区间值上的Fuzzy关系方程

Ｆｕｚｚｙ关系方程Ａ。Ｘ＝Ｂ中的矩阵Ａ、Ｂ的元素均为区间值，称为定义在区间值上的Ｆｕｚｚｙ关系方程。它是目前关于Ｆｕｚｚｙ关系方程理论研究中的主要问题之一￣［１］。本文讨论了区间值上Ｆｕｚｚｙ关系方程解的定义，并用符号定值法求出其全体解集。     

Associative monotonic operations in fuzzy set theory

The properties of binary operations in a real interval are considered and used in the discussion of generalized operations on fuzzy sets, on fuzzy numbers and on fuzzy probabilistic sets.     

A characterization of fuzzy subgroups

An ordinary subgroup of a group G is (1) a subset of G, (2) closed under the group operation. In a fuzzy subgroup it is precisely these two notions that lose their deterministic character. A fuzzy subgroup μ of a group (G,·) associates with each group element a number, the larger the number the more certainly that element belongs to the fuzzy subgroup. The closure property is captured by the inequality μ(x · y)?T(μ(x), μ(y)). In A. Rosenfeld's original definition, T was the function ‘minimum’. However, any t-norm T provides a meaningful generalization of the closure property. Two classes of fuzzy subgroups are investigated. The fuzzy subgroups in one class are subgroup generated, those in the other are function generated. Each fuzzy subgroup in these classes satisfies the above inequality with T given by T(a, b) = max(a + b ?1, 0). While the two classes look different, each fuzzy subgroup in either is isomorphic to one in the other. It is shown that a fuzzy subgroup satisfies the above inequality with $\text{T =}\text{‘minimum’}$ if and only if it is subgroup generated of a very special type. Finally, these notions are applied to some abstract pattern recognition problems.     

The structure of relations in personnel management

This paper addresses the problem of defining and analyzing relations between finite sets which are involved in personnel management.Personnel management criteria are imprecise due to the complex nature of the requirements and the difficulties to deal with personnel characteristics. Fuzzy set theory seems to be an efficient tool for considering these imprecisions. According to this idea the relations involved in personnel management can be seen as fuzzy relations.R.H. Atkin has formulated the abstract simplicial complex, achieving a structure which permits a deep knowledge of non fuzzy relations. In a sense this structure can be interpreted as a geometrical multidimensional one. Our purpose is to set up a multidimensional structure associated with the fuzzy relations which appear in personnel management.By means of an analysis of the above structure it is possible to study problems concerning the recruitment selection and promotion of personnel.