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。     

Reducing system of parameters and the Cohen-Macaulay property

Let R be a local ring and let (x ₁, …, x _r) be part of a system of parameters of a finitely generated R-module M, where r < dim_R M. We will show that if (y ₁, …, y _r) is part of a reducing system of parameters of M with (y ₁, …, y _r) M = (x ₁, …, x _r) M then (x ₁, …, x _r) is already reducing. Moreover, there is such a part of a reducing system of parameters of M iff for all primes P ε Supp M ∩ V _R(x ₁, …, x _r) with dim_R R/P = dim_R M − r the localization M _P of M at P is an r-dimensional Cohen-Macaulay module over R _P. Furthermore, we will show that M is a Cohen-Macaulay module iff y _d is a non zero divisor on M/(y ₁, …, y _d−1) M, where (y ₁, …, y _d) is a reducing system of parameters of M (d:= dim_R M).     

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.     

一般关系下的n-阶FC-粗糙集模型

给出一般模糊环境下n阶-FC-粗糙近似算子的定义,讨论它的一些性质,并通过α-水平集给出各种n-阶模糊粗糙集的表示。进而给出模糊传递闭包近似算子的定义,得到相应的结果。     

D.C.隶属函数模糊集及其应用(Ⅱ)--D.C.隶属函数模糊集的万能逼近性

本文是D．C．隶属函数模糊集及其应用系列研究的第二部分。指出在实际问题中普遍选用的三角形、半三角形、梯形、半梯形、高斯型、柯西型、S形、Z形、π形隶属函数模糊集等均为D．C．隶属函数模糊集，建立了D．C．隶属函数模糊集对模糊集的万有逼近性。探讨了D．C．隶属函数模糊集与模糊数之间的关系，给出了用D．C．隶属函数模糊集逼近模糊数的e-Cellina逼近形式，得到模糊数与D．C．函数之间的一个对应算子，指出了用模糊数表示D．C．函数的问题。     

Reservoir operations optimization via fuzzy criterion decision processes

In this paper, we propose the treatment of complex reservoir operation problems via our newly developed tool of fuzzy criterion decision processes. This novel approach has been shown to be a more flexible and useful analysis tool especially when it is desirable to incorporate an expert’s knowledge into the decision models. Additionally, it has been demonstrated that this form of decision models will usually result in an optimal solution, which guarantees the highest satisfactory degree. We provide a practical exemplification procedure for the models presented as well as an application example.     

模糊蕴涵与Smooth紧

1985年,Sostak[8]由逻辑的观点出发定义了一种基于Lukasiew icz蕴涵算子的Sm ooth紧,基于同样的思想A.H aydar E s[12]又定义了另外几种Sm ooth(fuzzy)紧并讨论了它们之间的关系。王国俊教授[10]提出了一种比Lukasiew icz算子具有更好性质的R0-算子,基于R0-算子我们定义了一种模糊蕴涵,通过这种模糊蕴涵定义几种Sm ooth紧并讨论了它们的一些性质。