网络信息污染综述

随着互联网技术的迅速发展和知识经济的到来,信息作为一种社会发展的战略资源,越来越受到人们的重视。由于网络环境下信息量的激增,信息传递的无序性和失控性,导致信息污染日益加剧,给社会造成了严重危害。因此,必须采取有效措施,进行网络环境下信息控污,净化网络信息空间,为更好地利用网络信息资源创造有利条件。针对网络信息环境,分析了信息污染的内涵、外在表现、污染原因,指出了信息污染的危害,给出了相关的解决对策。     

多波前算法在电力系统分析计算中的应用

以IEEE检验系统为例,通过数值试验将多波前算法与电力系统分析中常用的稀疏三角分解技术进行对比分析。数值试验结果表明,在串行计算平台上,多波前算法相对于稀疏三角分解技术具有更好的计算效率,因而更适合于现代大规模电力系统的分析计算。此外,多波前算法更易于并行化,而且是一种适合于可重构计算系统的新方法。     

系数为对称梯形模糊数的模糊线性规划

针对模糊系数的线性规划, 提出了一种系数为对称梯形模糊数的线性规划的方法, 同时得出一些定理、命题以及相应的算法, 并通过实例验证了该方法的有效性. 该方法与常规方法的不同之处在于无须将模糊线性规划转化为经典线性规划就能得到满意的模糊优化解, 因此提出的方法所取得的规划结果更加满足决策者的需要.     

基于遗传算法求解两曲线间最短距离

针对传统算法求解平面两条曲线间最短距离较为困难的问题,提出一种基于遗传算法的求解方法.该方法通过交替求解一条曲线上样本点到另一条曲线上样本点之间最短距离的方式对问题的可行域进行优化搜索.并对传统遗传算法做了两方面的改进,一是根据曲线自身特征分区间选取初始种群,使其能够合理地分布在寻优空间;二是对交叉结果进行跟踪,确保交叉成功后的个体优于父代个体.最终实例验证结果表明,该算法能较好地收敛到此类问题的全局最优解.     

Adaptive control design for a class of nonsmooth nonlinear systems with matched and linearly parameterized uncertainty

This paper presents an adaptive control design for a class of nonsmooth nonlinear systems with matched uncertainty, which is linearly parameterized with a known discontinuous function. The design framework is based on the concept of the Filippov solution as the classical Lyapunov theory for smooth systems cannot be applied to establish the stability of the adaptive control system due to the presence of the discontinuity. It is proved that as an adaptive control system, the global Lyapunov stability with the convergence of the state of the controlled system to the origin can be achieved by evaluating the monotonicity of the Lyapunov function in the state space, particularly on the discontinuous surface, while the uniqueness of the solution of the closed‐loop system is not necessarily guaranteed. Some interesting numerical examples are demonstrated with simulation results. Copyright © 2008 John Wiley & Sons, Ltd.     

Stability of solutions of stochastic functional-differential equations with poisson switchings and entire prehistory

The Markov properties of the solutions of Ito-Skorokhod stochastic functional-differential equations (SFDEs) with entire prehistory are considered, the concept of a weak infinitesimal operator is introduced for a Markov process that is a solution of an SFDE, and the strong solution of the SFDE is analyzed for stability. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 123–134, January–February 2009.     

Choosing the parameter of a modified additive-averaged splitting algorithm

The problem-solving time and the solution accuracy are expressed as functions of a parameter. An optimization problem of choosing the parameter using a “time cost–solution accuracy” criterion is considered. A Pareto-optimal set of solutions is obtained. The best value of the parameter is chosen by the ideal-point method. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 98–105, July–August 2009.     

A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products

Manufacturing systems produce their products by making use of three main strategies: make-to-order, make-to-stock and hybrid (combination of MTO and MTS strategies) systems. Hence, several products must be considered and partitioned in terms of many different conflicting criteria, leading to a large set of subjective or ambiguous data. Thus, an effective evaluation approach is essential to improve decision quality. In this paper a comprehensive decision, making structure is proposed to choose the proper strategy for producing the products. It consists of a novel hybrid methodology, which combines analytical hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) for partitioning of products. In this study, the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore, fuzzy AHP methodology is applied to determine the weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

基于改进的基因表达式编程算法在作业车间调度问题中的应用

文章提出一种新颖的方法一改进的基因表达式编程算法来求解作业车间调度问题。作业车间调度问题是许多实际生产调度问题的简化模型,基因表达式编程算法结合了遗传算法和遗传编程的优点,具有更强的解决问题能力,对基因表达式编程算法进行改进使其在作业车间调度问题的应用上更加有效;最后应用一个实例来验证提出方法的有效性。