基于动态模糊综合评判的故障预测方法

根据故障预测的特点和要求，指出传统模糊综合评判方法的不足，提出了动态模糊综合评判方法，给出了动态权重矩阵和动态模糊关系矩阵的确定方法。并与规则推理相结合，以反后座装置为例对评判过程予以说明，证明了该方法的有效性和实用性。     

电子商务环境下信用评级的一种新方法

为提高电子商务环境下信用评价水平，构建了一套完整的电子商务环境下信用指标体系，提出了一种基于拉开档次机理的模糊综合评判法，该方法改进了传统的拉开档次法．将其用在评价指标权重的确定上，采用模糊综合评判法对各指标值进行融合．结果表明，基于拉开档次机理的模糊综合评判法能够放大不同电子商务主体的信用差距，达到鼓励电子商务环境下基于信用机制的竞争的效果．该方法适用于需要放大被评价对象间差异的情形．     

基于分布估计算法的磁浮列车故障综合评判

针对使用传统模糊综合评判方法进行故障级别评判时模型参数难以确定的问题.提出一种基于分布估计算法(EDA)的模糊综合故障评判方法.该方法利用EDA进行模糊评判模型的进化学习,能有效实现模糊模型参数的自动优化,并具有模型易于理解、计算效率高的优点.通过对磁浮列车悬浮系统的仿真实验,结果显示基于分布估计算法的模糊故障综合评判方法能获得优于传统进化算法和其他机器学习方法的评判效果,具有较好的应用价值.     

基于模糊Petri网模型的路由选择

分析了影响通信系统性能的因素，力求在实时综合性能的基础上选择通信路由，论述了传统Petri网和模糊Petri网的一些基本概念和特点及其区别，描述了用模糊Petri网进行系统综合性能分析时的有效算法，提出一种基于综合性能的路由选择算法，最后通过实例来说明通信路由综合性能评价以及路由选择方法。     

双基色LED图文显示屏工作性能的综合评定

利用模糊综合评价方法，从新的角度——模糊失效准则出发，对ＬＥＤ显示屏的工作性能进行模糊评价，其中包括ＬＥＤ显示屏的模糊工作可靠性和图像质量两部分，最终得出贴近ＬＥＤ显示屏真实工作状况的模糊评价结果。     

处理复杂模糊系统的模糊穴映射方法

在对模糊穴和模糊穴空间等基本概念作一简单介绍之后，本文着重从模糊多变量系统的建模，辨识和控制等方面出发概述了基于模糊穴射的理论和方法，本文的方法有效地处理多变量模糊系统和利用已有的传统方法来解模糊系统问题开辟了一条新的途径，本文建立的方法的有效性已补实际的应用所证明。     

基于层次分析法的模糊分类优选模型

不同的模糊分类算法在同一个数据集合上常会产生不同的模糊分类．究竟哪种方法最能揭示数据的真实结构，对此，以模糊分类有效性指标为评价指标，应用层次分析法对各模糊分类进行综合评价，建立了一个模糊分类优选模型．大量实验表明，该优选模型所选出的最优模糊分类，其模式识别率高，能揭示数据的真实结构．     

智能题库的模糊设计与分析

本文对影响试卷内容难度的要素进行了系统的分析，采用模糊方法对试题内容难度进行统计评价，以模糊变换理论对多相相关要素加以综合考虑，引入隶属度不表述它们对试卷难度的影响程度，并以此确定影响试卷难度的主要要素，这种方法提高了现有标准化试题库的智能性、灵活性和可靠性，进而增强了综们的适用性。     

模糊判断矩阵环境下的大型群决策方法

为解决大型的群决策问题,对传统的模糊C均值算法(FCM)进行了扩展。通过扩展的算法对专家个体模糊判断矩阵聚类,获取模糊划分矩阵和聚类原型,根据模糊划分矩阵确定类权重,进而利用WAA算子对聚类原型进行集结,求取群综合模糊判断矩阵。通过算例验证了该算法的可行性。     

基于模糊并行约简的模糊概念漂移探测

数据流挖掘是当前数据挖掘研究的一个热点,并且数据流的类型也不尽相同。利用模糊粗糙集和F-粗糙集的基本原理和基本方法,提出了一种对模糊型数据流进行模糊并行约简、删除冗余属性的方法,并运用模糊并行约简中属性重要性的变化探测模糊概念漂移现象。有别于传统方法,该方法利用模糊数据的内部本质特性对模糊概念漂移进行探测,并且通过实例验证其探测模糊概念漂移的可行性和有效性。     

基于模糊粗糙集和D-S证据理论的多源灌溉信息融合方法

针对多源灌溉信息决策过程中不确定性信息难以融合的问题,提出了一种基于模糊粗糙集和D-S证据理论相结合的决策融合方法。运用模糊粗糙集理论,建立基本概率分配函数,计算各灌溉因子与灌溉决策之间的依赖程度,构建多个融合灌溉因子对灌溉决策的识别框架;然后运用改进的D-S证据理论,进行多源灌溉信息决策层级的融合,最终解决不确定信息的表达和合成问题。应用上述方法对华北地区冬小麦土壤水分、光合速率和气孔导度等信息进行灌溉决策融合,结果显示：灌溉决策的不确定性由融合前的最高38%降至9.84%,该方法可有效地提高灌溉决策精度,降低灌溉决策的不确定性     

Multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets

In this paper, we present a new method for multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets, where interval-valued intuitionistic fuzzy values are used to represent evaluating values of the decision-maker with respect to alternatives. First, we propose a new method for ranking interval-valued intuitionistic fuzzy values. Based on the proposed fuzzy ranking method of interval-valued intuitionistic fuzzy values, we propose a new method for multicriteria fuzzy decision making. The proposed multicriteria fuzzy decision making method outperforms Ye’s method (2009) due to the fact that the proposed method can overcome the drawback of Ye’s method (2009), where the drawback of Ye’s method is that it can not distinguish the ranking order between alternatives in some situations. The proposed method provides us with a useful way for dealing with multicriteria fuzzy decision making problems based on interval-valued intuitionistic fuzzy sets.     

基于改进直觉模糊熵和信息集成算子的多准则群决策方法

针对直觉模糊环境下准则权重和决策者权重完全未知的群决策问题,提出了一种基于改进直觉模糊熵和信息集成算子的多准则群决策方法.首先,借助直觉模糊数、语言变量法和定量指标值转化公式,将决策者的初始评价准则值规范化;其次,引入改进的直觉模糊熵度量方法确定准则权重和决策者权重;进一步对直觉模糊决策矩阵用直觉模糊加权平均算子和直觉模糊有序加权平均算子进行信息集成,利用新的得分函数对备选方案排序择优.从理论上论证了该方法的可行性,结合算例验证了该方法的有效性.     

Fuzzy multiattribute group decision making based on intuitionistic fuzzy sets and evidential reasoning methodology

In this paper, we propose a new fuzzy multiattribute group decision making method based on intuitionistic fuzzy sets and the evidential reasoning methodology. First, the proposed method uses the evidential reasoning methodology to aggregate each decision maker’s decision matrix and the weights of the attributes to get the aggregated decision matrix of each decision maker. Then, it uses the obtained aggregated decision matrices of the experts, the weights of the experts and the evidential reasoning methodology to get the aggregated intuitionistic fuzzy value of each alternative. Finally, it calculates the transformed value of the obtained intuitionistic fuzzy value of each alternative. The smaller the transformed value, the better the preference order of the alternative. The proposed method can overcome the drawbacks of the existing methods for fuzzy multiattribute group decision making in intuitionistic fuzzy environments.     

FLM-TOPSIS: The fuzzy linguistic multiset TOPSIS method and its application in linguistic decision making

Linguistic decision making is an important subject in decision making, many interesting and important linguistic decision making methods have been proposed, in which, alternatives-criteria decision matrix are uniformly used to express linguistic assessments of alternatives provided by decision makers with respect to criteria. Alternatives-criteria decision matrixes have some limitations when we use them to distinguish distinct, partial unknown or hesitant linguistic decision making or carry out linguistic decision making in the huge amounts of decision information and alternatives. In this paper, we propose alternatives-linguistic terms decision matrix to represent linguistic assessments of alternatives, analyze advantages of the decision matrix in representing linguistic assessments and distinguishing distinct, partial unknown or hesitant linguistic decision making. To simple and fast fuse alternatives-linguistic terms decision matrixes, we further provide linguistic multiset or fuzzy linguistic multiset to represent linguistic assessments in alternatives-linguistic terms decision matrixes, analyze the function properties of the fuzzy linguistic multiset. Motivated by fuzzy multiset and the TOPSIS method, we develop the fuzzy linguistic multiset TOPSIS method for linguistic decision making, the method is mainly consisted of transformation, aggregation and exploitation phases. In transformation phase, linguistic assessments of alternatives are transformed into fuzzy linguistic multisets by using alternatives-linguistic terms decision matrixes. In aggregation phase, we use Union, Intersection and Sum operations of multisets to obtain the positive and negative ideal solutions of linguistic decision making, which are different with the positive and negative ideal solutions of the traditional TOPSIS method, in addition, we provide a pseudo-distance between two fuzzy linguistic multisets to fast fuse linguistic assessments of alternatives. In exploitation phase, we define a new closeness degree of alternative by using pseudo-distances between the alternative and the positive and negative ideal solutions, which can be used to obtain the set of most satisfying alternatives. We also design an algorithm to carry out linguistic decision making based on the proposed method. In cases study, we use two practical examples to illustrate the practicality of the proposed method and compare it with the symbolic aggregation-based method, the hesitant fuzzy linguistic TOPSIS method, the hesitant fuzzy linguistic VIKOR method and the probabilistic linguistic term sets TOPSIS method, results indicate that alternatives-linguistic terms decision matrix and fuzzy linguistic multiset are alternative, useful and flexible tools for linguistic decision method and the fuzzy linguistic multiset TOPSIS method is suitable to deal with partial unknown or hesitant linguistic decision making.     

Multiattribute decision making based on interval-valued intuitionistic fuzzy values

In this paper, we present a new multiattribute decision making method based on the proposed interval-valued intuitionistic fuzzy weighted average operator and the proposed fuzzy ranking method for intuitionistic fuzzy values. First, we briefly review the concepts of interval-valued intuitionistic fuzzy sets and the Karnik–Mendel algorithms. Then, we propose the intuitionistic fuzzy weighted average operator and interval-valued intuitionistic fuzzy weighted average operator, based on the traditional weighted average method and the Karnik–Mendel algorithms. Then, we propose a fuzzy ranking method for intuitionistic fuzzy values based on likelihood-based comparison relations between intervals. Finally, we present a new multiattribute decision making method based on the proposed interval-valued intuitionistic fuzzy weighted average operator and the proposed fuzzy ranking method for intuitionistic fuzzy values. The proposed method provides us with a useful way for multiattribute decision making based on interval-valued intuitionistic fuzzy values.     

基于群体一致性强度的模糊评估方法

针对模糊信息的定量评估难题, 在研究多属性决策问题的基础上提出基于群体一致性强度的模糊评估方法. 利用证据理论合成评估值后, 引入语义折扣因子的概念, 将区间评估信息转化为确定的评估值; 设计群体一致性强度 指标, 最优化语义折扣因子的取值, 使得评估方法能够体现评估中的主流意见; 通过软件可信评估实例验证了所提出方法可有效解决模糊评估信息的分析和合成问题.     

基于Vague集的模糊决策方法

目前在智能领域中对Vague集的研究已越来越广泛与深入．并运用于决策问题中．为了更加有效地进行模糊决策，提出了一个基于Vague集的模糊决策方法．在这个方法中，对约束条件，从它出现的可能性和不出现的可能性以及未知是否出现的可能性三个方面去综合处理．使得决策更加准确和有效．还给出了一个实例说明这种基于Vague集的模糊决策方法．这个基于Vague集的模糊决策方法的提出，为决策系统提供了一个有用的工具．     

加型Pythagorean模糊偏好关系的多属性决策方法

考虑Pythagorean模糊偏好关系的多属性决策问题,提出了加性Pythagorean模糊偏好关系的多属性决策方法。基于加性一致性Pythagorean模糊偏好关系提出一种新的Pythagorean模糊权重确定模型。给出了可接受加性一致性Pythagorean模糊偏好关系的定义,并针对不满足可接受加性一致性的Pythagorean模糊偏好关系,提出一种加性一致性调整算法。给出基于Pythagorean模糊偏好关系加性一致性的多属性决策方法,并通过实例分析提出的新方法的可行性和合理性。     

基于变精度粗糙直觉模糊集的决策规则获取

以直觉模糊目标信息系统为研究对象,以粗糙集和直觉模糊集为工具,以知识发现为目的,给出了从直觉模糊决策表中获取决策规则的一种有效方法。即通过对Pawlak粗糙隶属函数的定义进行推广,给出粗糙直觉模糊隶属函数,利用新的粗糙隶属函数,建立了变精度粗糙直觉模糊集模型。在此模型基础上定义了变精度粗糙直觉模糊集的近似质量和近似约简,由近似约简导出概率决策规则集,从而给出了直觉模糊决策表的概率决策规则获取方法。最后,以实例说明了这一方法的有效性。关键词：