Parameterized defuzzification with maximum entropy weighting function—Another view of the weighting function expectation method

This paper mainly extends the weighting function expectation method from fuzzy numbers to the ordinary fuzzy set, and regards it as a weighting function defuzzification method. Some properties are discussed in the defuzzification context. The traditional center of gravity (COG) defuzzification method is extended to the weighting function COG (WFCOG) defuzzification method, which can represent the decision maker’s subjective attitude. With the properties of the weighting function, a parameterized defuzzification method with maximum entropy weighting function is proposed. Then it is integrated with the basic defuzzification distribution (BADD) method, which can represent the decision maker’s valuation and confidential attitude respectively. The relationships between the weighted function BADD defuzzification method and some existing defuzzification methods are discussed. The COG, MOM (mean of maxima), FOM (first of maxima), LOM (last of maxima), MOS (mean of support), FOS (first of support), and LOS (last of support) all become special cases with specific valuation and confidential attitude parameters.     

第三类模糊事件的模糊概率

研究第三类模糊概率--模糊事件模糊概率的数学描述.在区间概率和第二类模糊概率的基础上,进一步给出了第三类离散型模糊概率的随机变量及其模糊分布函数和模糊分布列的定义和性质以及数字特征,并研究了连续型模糊概率随机变量的模糊数学期望和模糊方差的定义,进一步完善了模糊概率理论.     

Using fuzzy random variables in life annuities pricing

This paper develops life annuity pricing with stochastic representation of mortality and fuzzy quantification of interest rates. We show that modelling the present value of annuities with fuzzy random variables allows quantifying their expected price and risk resulting from the uncertainty sources considered. So, we firstly describe fuzzy random variables and define some associated measures: the mathematical expectation, the variance, distribution function and quantiles. Secondly, we show several ways to estimate the discount rates to price annuities. Subsequently, the present value of life annuities is modelled with fuzzy random variables. We finally show how an actuary can quantify the price and the risk of a portfolio of annuities when their present value is given by means of fuzzy random variables.     

A deteriorating multi-item inventory model with fuzzy costs and resources based on two different defuzzification techniques

Normally inventory models of deteriorating items, such as food products, vegetables, etc. involve imprecise parameters, like imprecise inventory costs, fuzzy storage area, fuzzy budget allocation, etc. In this paper, we aim to provide two defuzzification techniques for two fuzzy inventory models using (i) extension principle and duality theory of non-linear programming and (ii) interval arithmetic. On the basis of Zadeh’s extension principle, two non-linear programs parameterized by the possibility level α are formulated to calculate the lower and upper bounds of the minimum average cost at α-level, through which the membership function of the objective function is constructed. In interval arithmetic technique the interval objective function has been transformed into an equivalent deterministic multi-objective problem defined by the left and right limits of the interval. This formulation corresponds to the possibility level, α = 0.5. Finally, the multi-objective problem is solved by a multi-objective genetic algorithm (MOGA). The model has been illustrated through a numerical example and solved for different values of possibility level, α through extension principle and for α = 0.5 via MOGA. As a particular case, the results have been obtained for the inventory model without deterioration. Results from two methods for α = 0.5 are compared.     

Trapezoidal approximations of fuzzy numbers preserving the expected interval — Algorithms and properties

Fuzzy number approximation by trapezoidal fuzzy numbers which preserves the expected interval is discussed. Algorithms for calculating the proper approximations are proposed and some properties of the approximation operators are discussed. It is shown that an adequate approximation operator might be chosen through the comparisons of some characteristics of the fuzzy number, like its ambiguity, width, its value and weighted expected value.     

模糊子群直积的若干性质

在Ray的论文[Onproduct of fuzzy subgroups105（1999）181—183]中，作者给出了模糊子群直积在min下的一些性质。在本文中我们将给出更多关于模糊子群直积的性质，并推广到模糊子环上；最后讨论了模糊子群的直积在t-模下的一些性质。     

一类模糊线性规划模型的模糊最优区间值

讨论一类既有模糊不等式约束又有模糊等式约束的全模糊系数线性规划问题。在给定的模糊隶属度水平下 ,将模型转化为区间数线性规划模型 ,通过确定区间模型的最佳目标函数和最大可行域以及最劣目标函数和最小可行域 ,求出目标函数的模糊最优区间值 ,从而为决策者提供更多的决策信息。最后给出一个数值例子。     

模糊均衡问题的求解及应用

根据实际均衡问题研究的需要,给出了模糊向量、模糊值函数、模糊矩阵等新概念,建立了模糊均衡问题的数学模型,即模糊线性互补问题。在引入新的模糊期望的基础上,研究了其性质,并据此给出了模糊线性互补问题的一种确定型等价式及此类问题的均衡解的概念。用实例说明了所提模型和方法的合理性及应用前景。     

Imprecise set and fuzzy valued probability

Set valued probability and fuzzy valued probability theory is used for analyzing and modeling highly uncertain probability systems. In this paper the set valued probability and fuzzy valued probability are defined over the measurable space. They are derived from a set and fuzzy valued measure using restricted arithmetics. The range of set valued probability is the set of subsets of the unit interval and the range of fuzzy valued probability is the set of fuzzy sets of the unit interval. The expectation with respect to set valued and fuzzy valued probability is defined and some properties are discussed. Also, the fuzzy model is applied to binomial model for the price of a risky security.     

模糊密度随机变量的数学描述

研究了由于概率密度函数的模糊性而引起的模糊概率随机变量问题。给出了区间密度函数、模糊密度函数、模糊密度随机变量及其分布函数和模糊密度随机变量的模糊数学期望、模糊方差等基本概念及定义和计算方法,并证明了有关定理。     

模糊子模函数与模糊秩函数

讨论模糊集合的一些性质;再以一般子模函数为蓝本,定义模糊子模函数,研究模糊子模函数和模糊秩函数的性质;然后利用这些性质推广通过模糊秩函数确定模糊拟阵的一个重要定理。     

模糊粗糙集的模糊邻域算子刻画

在模糊集合的公理化定义及其直积的基础上，提出基本模糊点的模糊邻域算子概念。用模糊邻域算子来定义模糊集的上近似和下近似。可以用模糊集的上、下近似来刻画模糊关系的自反性、对称性和传递性等性质。在模糊粗糙集的模糊邻域算子定义下，模糊粗糙集与粗糙模糊集可以统一起来。     

一般模糊近似算子的公理化刻画

给出无限双论域上一般模糊近似算子的构造性定义,叙述一般模糊近似算子的基本性质。引入邻域有限模糊关系的概念,利用上、下模糊粗糙近似的截集性质,给出一个刻画模糊近似算子的新公理,得到不同于以往的刻画模糊近似算子的公理集。     

区间值模糊数与区间值粗糙模糊数

把经典Z.Pawlak粗糙集与区间值模糊集相结合,研究区间值模糊数的基本理论.讨论区间值模糊数的基本性质和四则运算法则及其与其它各种区间数的关系,并给出区间值模糊数的刻画定理.同时,在经典Z.Pawlak粗糙集的框架下定义实直线上的粗闭区间套,提出区间值粗糙模糊数的定义.利用模糊数的表现定理给出区间值粗糙模糊数的一个刻画.     

Approximation of fuzzy numbers by trapezoidal fuzzy numbers preserving the expected interval

The problem to find the nearest trapezoidal approximation of a fuzzy number with respect to a well-known metric, which preserves the expected interval of the fuzzy number, is completely solved. The previously proposed approximation operators are improved so as to always obtain a trapezoidal fuzzy number. Properties of this new trapezoidal approximation operator are studied.     

Fuzzy expectation values in multistage optimization problems

The study demonstrates the use of fuzzy expectation values in problems of multistage optimization under uncertainty. A practicable procedure is presented for the case where the optimization objective can be decomposed into a series of single-stage decision goals. Instead of probability theory, the uncertainty resolution is accomplished by fuzzy expectation values. In essence, then, the risk aversion is emboided in the selection of the fuzzy integration measure. If for example, the primary goal of the optimization is to achieve a strict cost minimum, then in the lack of information, a weaker goal can be introduced that corresponds to balancing the anticipated costs to the risk of exceeding these in reality. In a number of common optimization problems the method proposed facilitates a rapid solution with clear information on the risk involved.     

定义在复数上的复模糊值函数

把所有的关于y轴对称的模糊数都定义为零模糊数,则两个相同的模糊数的差为零,利用~ar-+~ar+这样一个数值来描述模糊数的序关系,就可以得到关于纵向对称的模糊数都是等同的.在此基础之上对实模糊数的模糊距离及极限进行了研究.并研究了复模糊数的距离与复模糊数列的极限以及复模糊值函数的极限.将研究的复模糊值函数是定义在复数集C上取值于F(C)(所有的复模糊数的集合)中的复模糊数的函数.在新的序关系意义下讨论复模糊值函数的极限,并讨论复模糊值函数的收敛性质及Cauchy收敛判别法等.     

Some remarks on distances between fuzzy numbers

In this paper we consider different approaches to assigning distances between fuzzy numbers. A pseudo-metric on the set of fuzzy numbers arising from the idea of the value of a fuzzy number is described, and some of its topological properties are noted. Reducing functions are used to define a family of metrics on the space of fuzzy numbers; some convergent properties for these metrics are illustrated. Finally, a fuzzy distance between fuzzy numbers is introduced and its basic properties are studied.