Multi‐agent distributed intelligent system based on fuzzy decision making

Generally decision making for solving ill‐structured problems in DSS takes place in uncertain situations. The main drawbacks of existing traditional DSS are inefficiencies associated with dealing with complex models and large databases. Usually a fuzzy DSS has many input variables and, hence, its knowledge base, containing the totality of fuzzy rules, is very large. Large rule base leads to disadvantages in speed, reliability, and complexity of DSS. This paper introduces an alternative concept for designing fuzzy DSS based on multi‐agent distributed artificial intelligent technology and fuzzy decision making. The main idea of the proposed DSS is based on granulation of the overall system intelligence between cooperative autonomous intelligent agents capable of competing and cooperating with each other in order to propose a total solution to the problem and organization (combining individual solutions) of the proposed solution into the final solution. It is supposed that every agent in DSS is characterized by a set of fuzzy criteria of unequal importance and definition of a “winner” agent is based on multi‐criteria fuzzy decision making involving unequal objectives. © 2000 John Wiley & Sons, Inc.     

Adjoint-based fluid flow control and optimisation with lattice Boltzmann methods

A lattice Boltzmann (LB) framework to solve fluid flow control and optimisation problems numerically is presented. Problems are formulated on a mesoscopic basis. In a side condition, the dynamics of a Newtonian fluid is described by a family of simplified Boltzmann-like equations, namely BGK–Boltzmann equations, which are linked to an incompressible Navier–Stokes equation. It is proposed to solve the non-linear optimisation problem by a line search algorithm. The needed derivatives are obtained by deriving the adjoint equations, referred to as adjoint BGK–Boltzmann equations. The primal equations are discretised by standard lattice Boltzmann methods (LBM) while for the adjoint equations a novel discretisation strategy is introduced. The approach follows the main ideas behind LBM and is therefore referred to as adjoint lattice Boltzmann methods (ALBM). The corresponding algorithm retains most of the basic features of LB algorithms. In particular, it enables a highly-efficient parallel implementation and thus solving large-scale fluid flow control and optimisation problems. The overall solution strategy, the derivation of a prototype adjoint BGK–Boltzmann equation, the novel ALBM and its parallel realisation as well as its validation are discussed in detail in this article. Numerical and performance results are presented for a series of steady-state distributed control problems with up to approximately 1.6 million unknown control parameters obtained on a high performance computer with up to 256 processing units.     

OPTIMAL TRACKING CONTROL FOR DISCRETE TIME‐DELAY SYSTEMS WITH PERSISTENT DISTURBANCES

Optimal tracking control (OTC) for discrete time‐delay systems affected by persistent disturbances with quadratic performance indexes is considered. Optimal tracking controller is designed based on a sensitivity approximation approach. By introducing a sensitivity parameter, we transform the original OTC problem into a series of difference equations without time‐advance on time‐delay terms. The obtained OTC law consists of analytic feedback and feedforward terms, and a compensation term, which is the sum of the infinite series of adjoint vectors. The compensation term can be obtained with an iterated formula for the adjoint vectors. A simulation example shows that the approximation approach is effective in tracking the reference input and robust with respect to exogenous persistent disturbances.     

MarCHGen: A framework for generating a malware concept hierarchy

Automatic classification of virus instances into a concept hierarchy has been attracting much attention from malware research community. However, it is definitely not a trivial work, because malwares usually come in binary forms whose actions are complicated and obfuscated. Therefore, the typical data mining approaches based on feature extraction are not easily applied. In this paper, we tackle this problem by introducing a framework known as MarCHGen (Malware Concept Hierarchy Generation). In this framework, we first apply virus logical concept analysis, which incorporates formal concept analysis with temporal logic to capture malware behaviours and generalize a virus concept lattice accordingly. Second, we propose an on‐the‐fly conceptual clustering technique to generate a malware concept hierarchy. In the MarCHGen framework, the malware concept hierarchy will be monitored by the prelarge data set management technique to avoid reclustering several times unnecessarily. Our approach has been applied in a real data set of virus, and promising experimental results have been acquired.     

Non‐Zero Sum Differential Games of Backward Stochastic Differential Delay Equations Under Partial Information

In this paper, we study a new type of differential game problems of backward stochastic differential delay equations under partial information. A class of time‐advanced stochastic differential equations (ASDEs) is introduced as the adjoint process via duality relation. By means of ASDEs, we suggest the necessary and sufficient conditions called maximum principle for an equilibrium point of non‐zero sum games. As an application, an economic problem is putted into our framework to illustrate the theoretical results. In terms of the maximum principle and some auxiliary filtering results, an equilibrium point is obtained.     

Multi-adjoint t-concept lattices

The t-concept lattice is introduced as a set of triples associated to graded tabular information interpreted in a non-commutative fuzzy logic. Following the general techniques of formal concept analysis, and based on the works by Georgescu and Popescu, given a non-commutative conjunctor it is possible to provide generalizations of the mappings for the intension and the extension in two different ways, and this generates a pair of concept lattices. In this paper, we show that the information common to both concept lattices can be seen as a sublattice of the Cartesian product of both concept lattices. The multi-adjoint framework can be applied to this general t-concept lattice, and its usefulness is illustrated by a working example.     

容差近似空间的广义概念格模型研究

在粗糙集合理论中,近似空间概念格之间存在着有趣的对应关系,利用概念格研究知识的约简和发现。更直观和更有效,但已有的概念格模型是基于近似空间的等价类划分的。等价类划分过于苛刻,扩展的基于容差关系的近似空间具有更广泛的意义,但目前未见有相应的格模型被提出。该文提出了容差近似空间的一种格模型,称为广义概念格,给出了定义,描述了建立方法和由它产生规则的原则,讨论了空间复杂性问题,并且与其它相近方法做了比较     

Shape design optimization of an expansion step in a channel with moving boundaries for a viscous flow

A shape design optimization problem for viscous flows has been investigated in the present study. An analytical shape design sensitivity expression has been derived for a general integral functional by using the adjoint variable method and the material derivative concept of optimization. A channel flow problem with a backward facing step and adversely moving boundary wall is taken as an example. The shape profile of the expansion step, represented by a fourth-degree polynomial, is optimized in order to minimize the total viscous dissipation in the flow field. Numerical discretizations of the primary (flow) and adjoint problems are achieved by using the Galerkin FEM method. A balancing upwinding technique is also used in the equations. Numerical results are provided in various graphical forms at relatively low Reynolds numbers. It is concluded that the proposed general method of solution for shape design optimization problems is applicable to physical systems described by nonlinear equations.     

Efficient solution of lattice equations by the recovery method Part I: Scalar elliptic problems

In this paper, an efficient solver for high dimensional lattice equations will be introduced. We will present a new concept, the recovery method, to define a bilinear form on the continuous level which has equivalent energy as the original lattice equation. The finite element discretisation of the continuous bilinear form will lead to a stiffness matrix which serves as an quasi-optimal preconditioner for the lattice equations. Since a large variety of efficient solvers are available for linear finite element problems the new recovery method allows to apply these solvers for unstructured lattice problems.     

Transformation of Nonlinear MIMO Discrete‐Time Systems into the Extended Observer Form

The paper addresses the problem of transforming discrete‐time multi‐input multi‐output nonlinear state equations into the extended observer form, which, besides the inputs and outputs, also depends on a finite number of their past values. Necessary and sufficient conditions for the existence of the extended coordinate transformation are formulated in terms of differential one‐forms, associated with the input‐output equations, corresponding to the state equations. The difference between the single‐input single‐output and multi‐input multi‐output cases is described. The applicability of the conditions is illustrated by an example.     

Developing knowledge‐based decision support systems in public sector administration: A case study in the treasury department,ministry of finance,Malaysia

Since its introduction in the early 1970s the Decision Support System (DSS) concept has attracted a lot of attention from academics as well as users from business organizations. The literature abounds with accounts of systems that are claimed to have used the concept. The common characteristics of most of these systems are that they rely heavily on the use of quantitative models. In ill‐structured and higher level decision making quantitative models are used in conjunction with the qualitative models; in these cases a different approach and method in DSS development needs to be adopted. The objectives of this paper are twofold: to give a brief overview of the concept of DSS and Knowledge‐Based Systems and to describe the approach adopted and experience gained in conceptual analysis and modelling of the decision making process in an attempt to develop a Knowledge‐Based Decision Support System for Public Sector Management.     

Fuzzy adjunctions and fuzzy morphological operations based on implications

The concept of adjunction plays an important role in mathematical morphology. If the morphological operations, dilation and erosion form an adjunction in a complete lattice, then they, as well as the closing and opening constructed by them, will fulfill certain required properties in an algebraic context. In the context of fuzzy mathematical morphology, which is an extension of binary morphology to gray‐scale morphology based on fuzzy set theory, we use conjunctions and implications to define fuzzy dilations and fuzzy erosions. In this paper, we investigate when these pairs of dilations and erosions form a fuzzy adjunction, which is also defined by an implication. We find that the so‐called adjointness between a conjunction and an implication plays an important role here. Finally, we develop a theorem stating that a conjunction that is adjoint with an implication cannot only be generated by an R‐implication but also by other implications. This allows the easy construction of fuzzy adjunctions. © 2009 Wiley Periodicals, Inc.     

The emerging role of DSS: From passive to active

Existing decision support systems (DSS) are passive in their operation; their sole aim is to help maintain the current position of the firm. Conversely, Information Technology has recently adopted a more active role in the corporate strategy. This suggests that DSS could also undertake a far more active stance by identifying gaps in existing operations and suggesting ways to strengthen the standing of the firm. We renamed DSS containing this characteristics as Active Decision Support Systems (or ADSS) to emphasize their new orientation. Managers draw on their knowledge to suggest ways of alleviating problems or exploiting opportunities, and to evaluate each alternative in relation to the corporate objectives. Patterns and alternatives must be identified and incorporated into the ADSS. They should then be compared with the current position of the firm in order to determine whether any such problems/opportunities exist. This paper proposes an approach for designing ADSS; it introduces a knowledge-based component within the DSS framework and applies the concept of triggers to control the invocation of rule sets. A logical structure for ADSS is provided and the system use is illustrated through an example of strategic management. Issues for future research are highlighted.     

Multiple Fuzzy Relation and Its Application to Coupled Fuzzy Control

Using semi‐tensor product (STP) of matrix, this paper investigates the fuzzy relation of multiple fuzzy and uses this to design coupled fuzzy control is designed. First of all, under the assumption that the universe of discourse is finite, a fuzzy logical variable can be expressed as a vector, which unifies the expression of elements, subsets, and fuzzy subsets of a universe of discourse. Then, the matrix expression of set mappings is naturally extended to fuzzy sets. Second, based on STP, logic‐based matrix addition and product are proposed. These are particulary useful for the calculation of compounded fuzzy relations. Third, a dual fuzzy structure is introduced, which assures the finiteness of the universe of discourse, and is used for fuzzification and defuzzification. Finally, using the results obtained, a new technique is developed to design a coupled fuzzy controller for multi‐input multi‐output (MIMO) systems with coupled multiple fuzzy relations.     

对一种基于多值逻辑阵列变换的加解密系统的破解

多值逻辑在计算机科学中的应用前景是极为广阔的,比如在密码学方面的应用。该文通过引入多值逻辑中的序列变换的定义,采用矩阵乘法进行推导计算,证明了对文献（1）中提出的数据加密与解密系统不难进行破解,所采用的是“已知明文攻击”的方法。因此,对于真正可靠的基于多值逻辑的数据加密解密系统,还有待于进一步的研究。     

广义线性系统模型跟踪控制的新方法

本文讨论广义线性系统的模型跟踪控制问题, 提出了一种新的设计方法,该方法无须对系统作状态变换,因而能保留系统模型所具有的物 理意义．文章证明了这种设计方法的状态变量都是有界的,并给出一个实际电路的仿真结果 来证实这种设计方法的有效性．     

DSS鲁棒性的模糊逻辑改进

DSS的设计中，决策模型或决策规则的构建都经常的涉及不确定性问题．而DSS的鲁棒性是衡量DSS解决不确定性问题的主要标志．本文针对这一问题，提出了一种基于模糊逻辑技术的DSS设计，并与传统的基于线形加权和法的DSS进行比较，显示其在鲁棒性方面的突出改进．     

Generating complete sublattices by methods of formal concept analysis

Abstract

We present a solution to the problem of finding the complete sublattice of a given concept lattice generated by a given set of elements. We construct the closed subrelation of the corresponding incidence relation whose concept lattice is equal to the desired complete sublattice. The construction does not require the presence of the original concept lattice. We introduce an efficient algorithm for the construction and give an example and experiments. We also study a related problem of characterizing complete sublattices of a given concept lattice that are given by a general subrelation of the incidence relation.     

粗糙本体构建的格-树转化方法

粗糙本体是处理不精确性信息的一种基础性工具,其存在形式是由粗糙概念和粗糙关系构成的树形结构。粗糙本体的具体形式因为参与构建的领域专家的不同而呈现多样性,然而同样也是由粗糙概念和粗糙关系构成的粗糙概念格却具有结构上的惟一性。粗糙本体的构建因而可以利用格和树的组成与结构的相似性,构建粗糙概念格,转化生成粗糙本体。探讨了格-树转化方法的实现步骤：构建粗糙概念格;聚类粗糙概念格中的粗糙概念生成粗糙概念树;转化粗糙概念树为粗糙本体。构建实例阐释了格-树转换方法的具体应用。     

基于面向属性(面向对象)概念的对象粒的属性逻辑公式描述

研究基于面向属性概念、面向对象概念的对象粒的属性逻辑公式描述问题,讨论共有属性概念格和面向属性概念格、面向对象概念格的关系,在基于概念格的共有属性分析的对象粒描述方法基础上,给出基于面向属性概念格的可能属性分析的对象粒描述和基于面向对象概念格的必然属性分析的对象粒描述,分析属性逻辑公式语义构成的面向属性概念的外涵、面向对象概念的外涵的属性逻辑公式的结构特征,有助于应用对象粒的属性逻辑公式描述构建面向属性和面向对象的概念格.