具有(F(V×V),R,→,■)模糊逻辑模型的稳定性结构

本文利用多边矩阵理论定义的正交性及对称性,给出了一种具有两种因果关系的模糊稳定性逻辑分析模型,这种稳定的逻辑分析模型结构清晰、简单,并且可用于解决许多复杂问题.     

Fuzzy集的基数

关于Fuzzy集的基数，[1]中曾对有限支集的Fuzzy集以及极苛刻条件下的无限Fuzzy集给出过一种定义。但是，正如本文将要指出的那样，该定义是不合理的。本文将从研究Fuzzy映射入手，给出Fuzzy集基数的一般性定义。基于这一定义，不但得到有关基数的大部分结论，而且有其自身的特殊性。     

因素空间与概念内涵的表示

本文综合应用因素空间、信息系统和重于关系的方法,讨论了概念的内涵表示及其他有关问题。特别是,对在描述概念问题中不同于内涵和外延的第三种方法,即典型示范表示做了进一步的分析。     

模糊数序列的收敛性

探讨L-R型模糊数序列的S-和问题，定义关于模糊数的模糊小于的概念，在此基础上探讨模糊数的有序性，模糊数的截集函数的连续性，模糊数的格结构以及模糊数序列的收敛性等重要性质。     

模糊值Choquet积分(Ⅱ)--函数关于模糊值模糊测度的Choquet积分

研究一种取值于模糊数集的Choquet积分，该积分的被积函数是单值函数，所用的测度是模糊值模糊测度。给出其定义、性质和收敛定理。     

一种基于代价函数和模糊熵的图像分割方法

提出了一种基于代价函数和模糊熵的图像分割方法.该方法先用代价函数最小化法对退化的图像作预处理,之后,利用模糊熵作进一步的处理.实验结果表明:新方法和一般的阈值分割方法相比,不但分割图像的错分率较小,而且图像的视觉效果也有较大的改善.     

Railway wheel fault diagnosis using a fuzzy-logic method

A simple method for diagnosis of railway wheel defects using fuzzy-logic is proposed. The method is based on vibration measurements at different train speeds on healthy wheels and wheels with defects known a priori. The measured vibrations are statistically analyzed and confidence intervals for healthy and defective wheels depending on train speed and frequency of analysis are established. To facilitate the implementation of the method a fuzzy-logic is adopted. The fuzzy-logic model stores the obtained experience in a database and performs the decision making on damage extent and consequently the need of preventive maintenance. In view of the obtained results, the advantages and the limitations of the proposed approach as well as suggestions for further improvements are presented and discussed.     

模糊半群上的模糊同余及其扩张

给出模糊半群上的模糊同余的概念，并进一步研究它的一些基本代数性质。同时研究带有模糊半群上的模糊同余扩张性质(FCEPF)的半群类，得到一个半群有模糊半群上的模糊同余扩张性质、有模糊同余扩张性质(FCEP)、有同余扩张性质(CEP)三个条件是等价的。     

Rough隶属函数关于集合并与交的一种高精度计算方法

近些年来，许多处理近似问题的方法陆续被提出，其中利用Rough集理论计算两个集合的并和交的Rough隶属函数方法是被用较多的一种方法，但毕竟该方法精度较差。为此，介绍了一种精度较高的计算两个集合的并和交的Rough隶属函数方法，它克服了前者利用Rough集理论计算Rough隶属函数的复杂性，而迎来了简单和高精度的特点。     

Long-range predictive adaptive fuzzy relational control

A class of long-range predictive adaptive fuzzy relational controllers is presented. The plant behavior is described over an extended time horizon by a fuzzy relational model which is identified based on input-output closed-loop observations of the plant variables. In this class of adaptive controllers the control law attempts to minimize a quadratic cost over an extended control horizon. When used with linear models, this approach has revealed a significant potential for overcoming the limitations of one-step ahead schemes, such as the stabilization of non-minimum phase plants. Here, a uniform framework is adopted for implementing both the fuzzy model and the fuzzy controller, namely distributed fuzzy relational structures gaining from their massive parallel processing features and from the learning capabilities typical of the connectivist approaches. Issues such as maintenance during the adaptation process of the meaning of linguistic terms used at both fuzzy systems interfaces are addressed, namely by introducing a new design methodology for on-line fuzzy systems interface adaptation. The examples presented reinforce the claim of the usefulness of this new approach.