Detection of functional states by the ‘LAMDA’ classification technique: application to a coagulation process in drinking water treatment

The present Note proposes a learning classification methodology to identify functional states on a coagulation process involved in drinking water treatment. In this work, we chose to carry out the supervised control of this process while using the LAMDA (Learning Algorithm for Multivariate Data Analysis) classification technique. The LAMDA classification technique proposes the interactive participation of the expert operator during the learning phase and in the optimisation of the classification. In this work, all information stemming from the environment process as well as expert knowledge has been aggregated and exploited. The application chosen for state identification is the Rocade drinking water treatment plant located at Marrakech, Morocco. To cite this article: B. Lamrini et al., C. R. Physique 6 (2005).     

连续论域上Fuzzy集的信息熵

在文献[1]的基础上,把模糊熵从离散论域推广到连续论域,给出连续论域上Fuzzy集的偏熵、关联熵等概念。对其主要性质进行讨论,取得了一些令人满意的结果。拓宽信息熵的研究领域,对不确定复杂系统的信息处理、知识学习、归纳学习、模糊信息学的进一步研究打下一定基础。     

基于模糊一致矩阵法的优选炮阵地模型研究

运用基于模糊一致矩阵元素与权重关系式的排序方法,建立了一个基于模糊一致矩阵法的优选炮兵阵地的数学模型,具有较强的可操作性,利于计算机实现,可为实现炮兵作战自动化指挥提供有力支持.     

Fuzzy relation equations theory as a basis of fuzzy modelling: An overview

We give a wide overview on the applications of fuzzy relation equations theory to decision-making processes, to the construction of preference relations and to Knowledge Engineering, mainly fuzzy control and fuzzy pattern recognition. General theoretical results and methodological aspects are pointed out.     

θ-Fuzzy关系方程的分解与求解

在有限论域上首先给出θ-Fuzzy关系方程的分解，然后针对NR-蕴涵θ，探讨θ-Fuzzy关系方程的求解问题，基于解矩阵给出解的存在性的几个新判据，并在解集非空时，证明θ-Fuzzy关系方程的每一个解都存在一个极大解。     

三角模糊数互补判断矩阵的一种排序方法

给出三角模糊数互补判断矩阵的概念及三角模糊数相互比较的可能度公式 ,提出一种基于可能度的三角模糊数互补判断矩阵排序方法 ,通过算例说明该方法的可行性和有效性。     

The fuzzy supersphere

We introduce the fuzzy supersphere as sequence of finite-dimensional, noncommutative ₂-graded algebras tending in a suitable limit to a dense subalgebra of the ₂-graded algebra of ^∞-functions on the (2|2)-dimensional supersphere. Noncommutative analogues of the body map (to the (fuzzy) sphere) and the super-deRham complex are introduced. In particular we reproduce the equality of the super-deRham cohomology of the supersphere and the ordinary deRham cohomology of its body on the “fuzzy level”.     

基于Type-2型模糊集的动态生态位模型

复杂生态系统中,由于生物进化的高度非线性,使生物更容易适应环境的变化,生物与环境的交流要求用动态的观点来描述生态位及其相关概念。本文利用T ype-2型模糊集合的“宽带”效应,给出了具有动态特性的生态位模型,并相应的给出宽度和重叠的计算公式。应用于植物的生态位宽度和重叠的计算,与已有公式结果的比较,本文提出的模型可以全面的给出了物种在每个资源状态下的情形,同时反应了物种与环境之间的互动交流。为生物系统的应用研究和理论研究提出统一的数学模型。     

Binary fuzzy goal programming

Goal programming is an important technique for solving many decision/management problems. Fuzzy goal programming involves applying the fuzzy set theory to goal programming, thus allowing the model to take into account the vague aspirations of a decision-maker. Using preference-based membership functions, we can define the fuzzy problem through natural language terms or vague phenomena. In fact, decision-making involves the achievement of fuzzy goals, some of them are met and some not because these goals are subject to the function of environment/resource constraints. Thus, binary fuzzy goal programming is employed where the problem cannot be solved by conventional goal programming approaches. This paper proposes a new idea of how to program the binary fuzzy goal programming model. The binary fuzzy goal programming model can then be solved using the integer programming method. Finally, an illustrative example is included to demonstrate the correctness and usefulness of the proposed model.     

A fuzzy goal programming method with imprecise goal hierarchy

Two most widely used approaches to treating goals of different importance in goal programming (GP) are: (1) weighted GP, where importance of goals is modelled using weights, and (2) preemptive priority GP, where a goal hierarchy is specified implying infinite trade-offs among goals placed in different levels of importance. These approaches may be too restrictive in modelling of real life decision making problems. In this paper, a novel fuzzy goal programming method is proposed, where the hierarchical levels of the goals are imprecisely defined. The imprecise importance relations among the goals are modelled using fuzzy relations. An additive achievement function is defined, which takes into consideration both achievement degrees of the goals and degrees of satisfaction of the fuzzy importance relations. Examples are given to illustrate the proposed method.