基于IGIFS关系与截集的区间灰数直觉模糊粗糙集模型及性质

在论述区间灰数直觉模糊集概念基础上,提出了区间灰数直觉模糊关系(IGIFS关系)与区间灰数直觉模糊等价关系概念,定义了基于区间灰数直觉模糊关系环境下的区间灰数直觉模糊粗糙集模型,并讨论了相关性质.在界定了区间灰数直觉模糊集关于区间灰数直觉模糊数截集概念的基础上,定义了区间灰数直觉模糊粗糙集上、下截集近似,给出了区间灰数直觉模糊粗糙集的截集表现定理.     

区间数相似度研究

对区间数相似性问题进行了探讨.定义了区间数相似度的概念,给出了度量区间数相似度的一个简洁公式,详细研究了它的一些优良性质,如:自反性、对称性和传递性等,并且研究了区间数相似度公式与区间数排序的可能度公式之间的关系,从而为区间数的实际应用奠定了理论基础.     

区间数Heronian平均算子

定义了区间数Heronian平均算子以及区间数加权Heronian平均算子,并探讨了它们的性质.然后,提出了区间数几何Heronian平均算子以及区间数几何加权Heronian平均算子,并研究了它们的性质.最后,将区间数加权Heronian平均算子和区间数几何加权Heronian平均算子应用于多属性决策,说明了它们的有效性.     

区间数的一种改进的排序方法

为了解决具有不确定性区间数的多属性决策问题 ,本文给出了区间数的一种简洁有效的排序方法 .我们首先引入了一个区间数大于另一个区间数的可能度概念 ,进而推出其有关性质 ,并对排序起着重要作用的结论给出了证明 .在此基础上本文还指出了区间数排序的一种简洁算法 ,使得对多个区间数的排序更为快捷有效 ,并通过实例加以验证 .     

区间数的绝对值与区间值函数的极限

研究了区间数的绝对值和区间值函数的极限问题.首先,讨论了区间数的H-差的性质,得到了H-差的两个运算法则;然后,给出了区间数的绝对值概念,并讨论了区间数绝对值的性质;最后,借助区间数的H-差和绝对值的概念,建立了区间值函数极限概念的一种新的表达方式,给出了极限存在的充分必要条件,证明了极限值的唯一性及对加法运算和数乘运算的封闭性.     

不确定多属性决策中区间数排序的一种新方法

根据格序决策理论,提出不确定多属性决策中区间数排序的新方法,将综合评价值区间数分为可比较与不可比较区间数,对可比较区间数利用区间数上界进行比较来排序,而对不可比较区间数利用均值及区间上界比较来排序,方法比格序决策法和期望-方差法等方法更加简单易行,进一步提高了决策效率.最后通过算例验证方法的可行性和有效性.     

区间数判断矩阵排序的χ2方法

提出了计算正数字矩阵排序向量的拟χ2方法及计算区间数判断矩阵排序向量的区间数χ2方法,讨论了区间数χ2方法的优良性质以及区间数χ2方法增加元素的保序性条件.     

基于灰色关联度的区间信息指派问题研究

研究了损益矩阵为区间数的不确定型指派问题,给出了区间数关联度的计算公式,提出了一种基于区间数关联度的区间信息指派方法,最后通过实例验证了该方法的实用性和有效性.     

基于二元联系数可能度函数的区间数排序方法及应用

针对因区间数排序方法差异或可能度函数失效带来的区间数排序结果与实际情况明显不符和保序性较差的问题,系统梳理两区间数在实数轴上相离、相交以及包含等三类6种位置关系,引入集对分析方法定义了区间数集对及其二元联系数,利用区间数长度、集对、同一集、差异集以及比较空间的3个特征量,构造了基于二元联系数的可能度函数,进而建立了基于二元联系数可能度函数的区间数排序方法,全面地反映和描述了区间数相对大小比较时的确定性信息与不确定性信息.通过二元联系数的可能度函数性质证明和实例分析,证明了二元联系数的可能度函数的有效性,也验证二元联系数可能度函数的区间数排序方法的保序性和广泛适用性.最后,将基于二元联系数可能度算法的区间数排序方法用于采矿方法优选中,证实了该方法的可行性和应用价值.     

区间数互补判断矩阵的性质及相关问题研究

研究了区间数互补判断矩阵的性质问题。利用区间数互反判断矩阵与区间数互补判断矩阵之间的转换关系，给出了乘性一致性与加性一致性区间数互补判断矩阵的定义，并研究了一致性区间数判断矩阵的一些特殊性质；同时给出了区间数互补判断矩阵满意一致性的一个简单的判断方法与算法。文章的最后，通过一个例子来说明这个算法的有效性。     

Bell-shaped Fuzzy Soft Sets and Their Application in Medical Diagnosis

A soft set theory is a new general mathematical tool to dealing with imprecision. The theory differs from traditional mathematical tools to dealing with uncertainties in which many mathematical theories failed. In this paper, we proposed the concept of Bell shaped fuzzy soft set and its application in medical diagnosis using arithmetic operations of discrete- Gaussian fuzzy number, triangular-Cauchy fuzzy number and Gaussian-Cauchy fuzzy number. As an integral part of this paper, we discuss the parametric form of Gaussian membership function is discussed with some important properties.     

A new fuzzy multi-objective programming: Entropy based geometric programming and its application of transportation problems

In this paper, we introduce a fuzzy mathematical programming with generalized fuzzy number as objective coefficients. We also examine a transportation problem with additional restriction. There is an additional entropy objective function in the transportation problem besides transportation cost objective function. Using new fuzzy mathematical programming, this multi-objective entropy transportation problem with generalized trapezoidal fuzzy number costs has been reduced to a primal geometric programming problem. Pareto optimal solution of the transportation model is found. Numerical examples have been provided to illustrate the problem.     

半群中的粗糙模糊理想及粗糙模糊素理想

将粗糙集的理论方法用于模糊半群的研究。给出上(下)粗模糊子半群及上(下)粗模糊左(右)理想、粗糙模糊素理想等概念,研究它们的有关性质。证明上粗模糊子半群与上粗模糊理想是通常的模糊子半群与模糊理想概念的扩张。     

The influence of some fuzzy implication operators on the accuracy of a fuzzy model-part II

The influence of fuzzy implication operators and the connective Also on the accuracy of a fuzzy model of a d.c. series motor is considered. Some typical fuzzy implication operators are applied to the construction of a fuzzy model of a d.c. series motor. A root-mean-square error is used as the criterion of the fuzzy model's adequacy to the real system. A number of mathematical operations necessary for the implementation of the fuzzy model are used as the criterion by which the fuzzy model's applicability if estimated from the point of view of computing techniques. The best types of fuzzy relations, representing fuzzy models of a real system, are chosen in order to secure the least root-mean-square error with minimal number of mathematical operations necessary for computer implementation.     

模糊量及模糊数的表现特性

模糊集的表现定理是模糊数学的最基本理论.在表现定理的基础上,对各种模糊量:包括凸模糊量、正规模糊量、正规凸模糊量、凸有界模糊量、模糊数、有限模糊数、对称模糊数的表现定理进行了深入的研究,从而建立了不同类型模糊量与普通集合之间的联系.     

公务员招聘的模糊决策模型

运用模糊数学理论与多目标决策模糊优化方法,在不考虑应聘人员的意愿及在考虑应聘人员意愿和用人部门的希望要求的情况下,择优按需录用.分别建立相应的模型.其结果令人满意,具有较强的可靠性和适用性.     

Fuzzy理论在工程环境灾害预测中的应用

针对矿山大型排土场所出现的滑坡等工程环境灾害的预测与防治问题,着重探讨排土场边坡失稳破坏预测问题.文中采用Fuzzy数学中的Fuzzy概率测度理论建立理论预测分析模型,并对大型排土场边坡失稳破坏的Fuzzy概率测度进行具体的预测分析,所获结果与已有的经典分析方法所获理论结果一致.针对矿山大型排土场所出现的滑坡等工程环境灾害防治问题,提出了具体的防治技术措施.     

The systems approach and fuzzy set theory bridging the gap between mathematical and language-oriented economists

Ideas are presented to show how fuzzy mathematics can be applied in macro-economics in combination with the systems approach in order to bridge the gap between mathematical and language-oriented economists.Two reasons are given.From a mathematical point of view, fuzzy sets, fuzzy relations and fuzzy logic are not fuzzy at all. They are all well defined, but tend to be more complicated than traditional, mathematical concepts used in economics.From a language-oriented economist's point of view, fuzzy sets, etc. are used to express mathematically the type of concepts which are typical in language and most valuable in dealing with complex systems like an economy.The paper deals with economics in general terms, but examples are provided to illustrate the ideas.     

区间值模糊推理

针对区间值模糊关系,讨论区间值模糊关系的合成运算及其运算性质,在此基础上研究简单区间值模糊推理和多重区间值模糊推理的两种模糊推理形式,给出4种区间值模糊推理的数学模型,并辅以实例来说明我们提出的区间值模糊推理方法的可行性。     

Optimisation under hybrid uncertainty

Fuzzy Stochastic Optimisation is emerging as a subfield of Mathematical programming, the disciplinary matrix of which consists of analysis of mathematical programs under fuzziness and randomness along with methods for solving them. The “primum movens” of this paper is to describe a unifying methodological approach, that is suitable for finding a satisfying solution of a mathematical program in the presence of fuzzy data and random variables. Properties of fuzzy random variables (FRVs) serve as the backdrop to this approach which also lends itself better to handling mathematical programs with fuzzy random coefficients. For the paper to be somewhat self-contained, the notion of FRV is briefly discussed and a synopsis of Fuzzy Stochastic Optimisation provided. A systematically solved example aimed at illustrating the proposed approach is also included.