在线仿真技术初探

本文提出了一种在线仿真技术，它通过网络将仿真系统与指挥决策系统连接起来，实现了仿真系统与指挥决策系统之间的实时信息流动，从而形成一种虚实结合的快速仿真决策系统。文章在讨论了模型的语义描述的基础上．还提出了基于HLA的模型的动态组合及动态仿真联邦的自动运行机制。     

基于DIS的防空训练空情保障系统

该文以新三打三防训练模拟为背景，建立了多种虚拟靶标，如巡航导弹、作战飞机、武装直升机的仿真模型，包括物理模型和决策模型，在此基础上，基于分布式交互仿真技术（Distributed Interactive Simulation,DIS）开发了一个用于防空训练模拟的空情保障系统。本文主要介绍了空情保障系统的模型建立、数据管理和系统集成方法。     

医院管理系统仿真模型的建立与实现

介绍了如何运用计算机仿真技术去实现一个辅助医院管理的仿真工具。通过对系统（医院）的分析,描述了仿真模型的建立和处理它的表示法,最后给出了仿真工具的实现,此工具可被运用于医院做决策过程的支持。     

智能决策系统中模型服务器的设计与实现

该文基于从定性到定量综合集成（Meta Synthesis)的思想，在XOD（X On Demand)应用体系结构中，为满足决策系统中按需仿真的需要，建立了SOD（Simulation On Demand)模型服务体系，提出了模型服务器的概念，分析了综合集成环境中模型服务器的功能和作用，同时，论述了模型服务器的内涵，组成。基于广域网应用环境，对模型服务器的结构进行了设计，并建立了SOD模型服务器工作机制，完成了模型服务器中数据转换功能。     

基于代理模型和遗传算法的仿真优化研究

首先由已知样本建立神经网络作为代理模型，替代费时的仿真评价而快速给出近似目标值；然后基于代理模型，采用GA进行决策量寻优．为增强优化结果的可靠性和一致性，讨论了按问题信息选取样本和多模型方法.基于典型压力管设计问题的数值仿真，验证了所提出方法的可行性和有效性，其结果明显优于现有文献结果.     

溢洪道开挖的面向对象建模与仿真

该文针对溢洪道施工的复杂性和重要性，论述了采用仿真技术研究溢洪道开挖的必要性，并运用面向对象的计算机建模技术与离散事件系统的仿真技术，建立了溢洪道开挖仿真模型，开发了相应的仿真软件^[4]，实现了开挖过程的仿真，最后，通过实例说明了开挖的仿真软件对施工组织决策的意义和作用。     

石油勘探开发系统动力学模型建立及应用

以X油田勘探开发实际数据为基础，运用系统动力学方法建立了石油勘探开发系统动力学模型，并进行仿真模拟。结果表明，该模型能够真实反映石油勘探开发实际，用于预测可以取得良好效果，有效提高决策的预见性和科学性。     

医药配送系统仿真模型及优化

物流配送已成为电子商务发展中的关键问题之一,也是供应链管理中的核心问题。该文利用仿真软件建立了包括制造商、医药分销中心和零售商的物流配送系统的仿真模型。通过对模型进行仿真可观察物流配送的动态运行情况,从而找到配送过程的瓶颈。在建立的仿真模型基础上及给定的约束条件下,通过构造目标函数对仿真模型进行了优化。通过优化,给出了医药分销中心最优的订购时间间隔和不同药品的最佳库存量,这为实际决策提供了正确依据。     

大坝施工仿真计算模型参数敏感性区间分析

模型参数是仿真计算的数据基础，而且不同的模型参数往往会导致不同的仿真结果。在考虑模型参数并非确定性的情况下。进行模型参数对仿真结果敏感性分析。以及在不影响仿真结果可行性或合理性的情况下确定模型参数的可行域，这无论对于仿真研究，还是指导决策活动都是十分重要的。     

图像处理技术在标定微观交通仿真模型中的应用

城市交通控制的许多决策都是基于微观交通流仿真模型进行的。文章研究应用了图像处理技术来对微观交通流仿真模型的参数进行标定，并使用模拟退火算法使仿真的结果和被仿真对象的实际观测数据吻合。     

The interactive consensus reaching process with the minimum and uncertain cost in group decision making

The consensus model with the minimum cost (or minimum adjustments or minimum information loss) is a powerful decision tool for consensus building in the group decision making (GDM). In the extant consensus models with the minimum cost, the unit adjustment cost of each expert is assumed to be exactly known, and an optimization-based consensus model is utilized to support the consensus building. In the practical GDM, however, it is difficult to obtain the exact unit adjustment costs, and the unit adjustment costs of experts are often uncertain. Moreover, we argue that the consensus cannot be achieved directly using the established optimization-based consensus model, because the consensus building is an interactive process that needs the participation of experts. This paper proposes an interactive consensus reaching process with the minimum and uncertain cost. In the consensus reaching process, an optimization-based consensus model with the uncertain unit cost is constructed to obtain the optimal adjusted opinions of experts. Then, the costs/resources are provided for experts to modify their opinions, and the obtained optimal adjusted opinions are used as a reference for the opinions-modifying in the consensus reaching process. Meanwhile, the unit adjustment costs of experts can be estimated according to the actual situation of the opinions-modifying in the consensus reaching process. The detailed numerical and simulation analysis are conducted to demonstrate the validity of the proposed consensus reaching model.     

A simulation study of logistics activities in a chemical plant

This article describes an application of discrete-event simulation to study logistics activities in a chemical plant. Most chemical production involves continuous flow of materials, such as liquid, gas or solid through the manufacturing and logistics processes. Some simulation issues in this area are conceptualizing production operations for simulation, discretization of continuous processes and building adequate level of detail in the models. The purpose of this study is to determine the required capacity of logistics operations to allow continuous operations of a chemical manufacturing plant. The application has been used to provide critical decision support. The value of the simulation study is not only the simulation model itself but also the process of building it.     

基于模糊判断矩阵的两阶段群决策方法

针对多属性群决策问题,提出一种两阶段决策分析方法。通过分析积型模糊一致性判断矩阵和模糊判断矩阵的排序向量之间的偏差,建立并求解一个规划模型,得到专家模糊判断矩阵的排序向量。由最小化专家模糊判断矩阵的排序向量与专家群组排序向量的偏差,再次建立并求解一个规划模型,得到反映专家群组偏好的排序向量,从而得出基于模糊判断矩阵的两阶段群决策方法。通过2个算例说明了该方法的可行性与有效性。     

基于K-means聚类与决策树的有线电视交互服务订制预测

建立了一种基于聚类分析与决策树分析相结合的服务订制预测模型,阐述了聚类分析K-means算法、决策树算法C5.0算法原理、建模流程的设计,将模型应用于某地区用户对有线电视交互服务的订制意愿预测,最终确定高响应率客户群.实验证明.该模型相对于仅通过决策树进行预测能更大程度地提高分类精度,并能更有效地识别出高响应率客户群.     

Learning decision rules for energy efficient building control

While rule based control (RBC) is current practice in most building automation systems that issue discrete control signals, recent simulation studies suggest that advanced, optimization based control methods such as hybrid model predictive control (HMPC) can potentially outperform RBC in terms of energy efficiency and occupancy comfort. However, HMPC requires a more complex IT infrastructure and numerical optimization in the loop, which makes commissioning, operation of the building, and error handling significantly more involved than in the rule based setting. In this paper, we suggest an automated RBC synthesis procedure for binary decisions that extracts prevalent information from simulation data with HMPC controllers. The result is a set of simple decision rules that preserves much of the control performance of HMPC. The methods are based on standard machine learning algorithms, in particular support vector machines (SVMs) and adaptive boosting (AdaBoost). We consider also the ranking and selection of measurements which are used for a decision and show that this feature selection is useful in both complexity reduction and reduction of investment costs by pruning unnecessary sensors. The suggested methods are evaluated in simulation for six different case studies and shown to maintain the performance of HMPC despite a tremendous reduction in complexity.     

Consensus-based decision support for multicriteria group decision making

Consensus decision making is complex and challenging in multicriteria group decision making due to the involvement of several decision makers, the presence of multiple, and often conflicting criteria, and the existence of subjectiveness and imprecision in the decision making process. To ensure effective decisions being made, the interest of all the decision makers usually represented by the degree of consensus in the decision making process has to be adequately considered. This paper presents a consensus-based approach for effectively solving the multicriteria group decision making problem. The subjectiveness and imprecision of the decision making process is adequately handled by using intuitionistic fuzzy numbers. An interactive algorithm is developed for consensus building in the group decision making process. A decision support system framework is presented for improving the effectiveness of the consensus building process. An example is presented for demonstrating the applicability of the proposed approach for solving the multicriteria group decision making problem in real world situations.     

基于VR的航天发射视景仿真系统设计与实现

针对如何构建一个虚拟的航天发射训练平台的现实问题,设计出一种基于虚拟现实技术(Virtual Reality,VR)的航天发射视景仿真系统;介绍了该视景仿真系统的逻辑结构和网络结构,采用三角形面片法构建发射场的地形地貌,并通过纹理映射使地形地貌更加逼真;利用图像和3D图形混合建模的方法构建发射场的设施;运用粒子系统原理,设计出发射火箭的火焰模型。通过Vega仿真软件进行系统集成和渲染,使整个仿真系统得到实现;实践证明,该仿真系统能够实时仿真卫星发射的全过程,为实时指挥、判读提供辅助决策支持平台,具有极大的应用价值。     

基于虚拟样机仿真的多管火箭武器专家系统

针对传统武器专家系统主要以武器专家经验为基础,存在着缺少动态预测功能及动力学机理性解释的不足,提出一种以多体系统动力学虚拟样机仿真模型为基础的多管火箭武器专家系统集成框架.通过建立多管火箭武器虚拟样机仿真模型,论述了该多管火箭专家系统的体系结构、系统框架、基于虚拟样机仿真的专家系统决策过程及参数推理与反演.在此基础上,通过关键技术实现与关键模块的系统开发,通过实例演算,验证了该系统模式的优越性,为解决武器系统分析提供了一个有效而又直观的新途径.     

Expertise-based consensus building for MCGDM with hesitant fuzzy linguistic information

The integration of a consensus reaching process (CRP) becomes paramount to make highly accepted group decisions in complex real-life multi-criteria group decision making (MCGDM) problems. Notwithstanding, existing CRPs for MCGDM do neither exhaustively analyse the diversity in decision makers’ expertise levels, nor they consider that (because of such diversity) individuals might exhibit distinct perceptions on the relative importance of evaluation criteria. In this study, we present a novel expertise-based consensus building model for MCGDM under a hesitant fuzzy linguistic setting. Firstly, an expertise identification approach is devised to objectively determine the expertise degree of each decision maker based on multiple features. The proposed approach allows to dynamically assigning importance weights to the decision makers’ opinions based on their expertise, as well as intelligently combining their individually elicited subjective and objective criteria weights into meaningful expertise-dependent combinative weights. Then, a CRP for MCGDM problems is introduced based on an improved consensus measurement process and an expertise-based feedback mechanism that provides a highly tailored, personalised means of direction rules to guide decision makers during the consensus building process. A numerical example is provided to illustrate the application of the CRP, and a detailed comparison analysis is presented to verify the validity and accuracy of this study’s proposal.