多阶段项目风险权衡模型

本文通过对风险概念的进一步分析,说明了风险权衡在项目风险分析中的重要作用。并且阐述了多阶段项目风险权衡的两个基本目的,即评估各阶段风险权衡策略的综合效果,以及根据预期风险控制要求,产生各阶段的风险权衡策略。同时,通过给出一些基本假设,引出了一个多阶段项目的风险权衡模型,并且给出了几种简单实用的求解方法：搜索法和启发式法等。最后,就本文所讨论的方法进行了简单的分析。     

有色噪声中多个周期相近信号参数的估计算法

本文提出了一种“谐波组清除算法”来估计周期信号的参数。该算法不仅计算简单并可获得较高的频率分辨率,而且对信号模型具有较强的鲁棒性。最后,用数值仿真数据与实测直升机噪声数据对该算法进行了检验。     

军用分布式交互仿真(DIS)原型系统的实现研究

讨论以军事训练为目的的分布式交互仿真技术,分析了ＤＩＳ设计需考虑的若干主要问题、一致通信环境、仿真应用开发的客户服务器环境,并在此基础上给出一个ＤＩＳ原型系统的网络结构、功能原理与性能分析。     

基于规则专家系统的广义随机Petri网仿真分析模型

利用广义随机Ｐｅｔｒｉ网为基于规则的专家系统建模,将推理过程中规则的匹配—选择—执行循环的各阶段统一于其广义随机Ｐｅｔｒｉ网模型中,通过对该模型的计算机仿真分析,可对系统的可靠性及性能进行评价。     

冷连轧过程线性化动态模型的研究

以多机架四辊冷连轧机为背景,研究了冷连忆过程的动态模型,建立了冷连轧过程的工作点线性化状态空间模型,实验仿真结果说明了这一动态模型的有效性。     

Non-fragile decentralized H∞ controller design for uncertain linear systems

Considering the design problem of non-fragile decentralized H∞ controller with gain variations, the dynamic feedback controller by measurement feedback for uncertain linear systems is constructed and studied. The parameter uncertainties are considered to be unknown but norm bounded. The design procedures are investigated in terms of positive definite solutions to modify algebraic Riccati inequalities. Using information exchange among local controllers, the designed non-fragile decentralized H∞ controllers guarantee that the uncertain closed-loop linear systems are stable and with H∞ -norm bound on disturbance attenuation. A sufficient condition that there are such non-fragile H∞ controllers is obtained by algebraic Riccati inequalities. The approaches to solve modified algebraic Riccati inequalities are carried out preliminarily. Finally, a numerical example to show the validity of the proposed approach is given.     

Exploration of TCM Masters Knowledge Mining

Traditional Chinese medicine （TCM） has a rich knowledge about human health and disease by its special way evolved along a very long history. As modern medicine is achieving much progress, arguments and disputes toward TCM never end. To avoid losing precious knowledge of living TCM masters, endeavors have been engaged to systematic collection of those knowledge of TCM masters, such as their growth experiences, effective practical cases toward diseases and typical therapeutic principles and methods. Knowledge mining methods have been expected to explore some useful or hidden patterns to unveil some mysteries of the TCM system. In the paper, some computerized methods are applied toward those collected materials about some living TCM masters in China mainland to show a different way of exposing essential ideas of those TCM masters by correspondence visualization which aims to help people understand TCM holistic views toward disease and body, and facilitate tacit knowledge transfer and sense-making of the essence of TCM. The work is one kind of qualitative meta-synthesis of TCM masters＇ knowledge.     

On-Line Scheduling of Unit Time Jobs with Rejection on Uniform Machines

The authors consider the problem of on-line scheduling of unit execution time jobs on uniform machines with rejection penalty. The jobs arrive one by one and can be either accepted and scheduled, or be rejected. The objective is to minimize the total completion time of the accepted jobs and the total penalty of the rejection jobs. The authors propose an on-line algorithm and prove that the competitive ratio is 1/2 （2 W √3） ≈ 1.86602.     

Application of improved equivalent edge currents in synthetic aperture radar imaging

Target modeling and scattering function calculating are important prerequisites and groundwork for the synthetic aperture radar (SAR) imaging simulation. According to the difficult problems that normal methods cannot calculate the scattering function of electrically large object under the condition to wideband, an effective method of improved equivalent edge currents is presented and applied to SAR imaging simulation for the first time. This method improves calculating velocity and has relatively high precision. The concrete steps of applying the method are given. By way of the simulation experiment, the effectiveness of the method is verified.     

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.