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．     

Globus支持下基于网格的开放式决策支持系统设计与实现

网格技术的出现和成熟将给决策支持系统(DSS)带来一场新的变革．提出了一种新型的DSS——基于网格的开放式决策支持系统(GBODSS)，它充分地利用了网格技术的优势，将网格技术和DSS结合在一起，并给出了该框架利用Globus工具的一种实现方案．     

中国测绘科学研究院为国办提供地理信息技术服务受到好评

近日国务院办公厅秘书局致函国家测绘局，对国家测绘局多年来支持“国办地理信息系统”建设，使地理信息技术进入了政府系统的信息化应用领域，在政府管理与决策中取得了突出成效给予好评。对直接参与这项工作的中国测绘科学研究院和有关地方部门表示感谢，并希望国家测绘局在“十一五”期间继续支持“国办地理信息系统”的技术开发工作，构建GIS、RS、GPS与DSS技术深度集成的具有完全自主知识产权的新一代政府管理与决策地理信息系统平台软件，满足不同类型、不同层次政府工作人员构建个性化地理信息应用的需要。     

宾馆决策支持系统的设计与应用

20世纪70年代，美国麻省理工学院的两位学者首次提出决策支持系统“Decision Support System”这一概念。经过二十多年的发展，DSS越来越广泛地应用到各个行业中，为决策者提供了一个崭新的决策辅助工具。但应用DSS系统有一个前提，就是一个企业必须有可供决策的数据。     

基于组件的决策支持系统模型设计与实现

决策支持系统（Decision Support System简称DSS）是模型驱动的，DSS中模型的设计与实现是一个有待进一步研究的问题。本文把组件技术引入到DSS模型的设计与实现中来，提出基于组件技术的DSS的模型设计与实现策略。给出基于组件思想的DSS模型定义和运算，并给出基于组件技术的DSS基模型和复合模型的实现方法。     

DSS中数据仓库的构建技术研究

主要研究基于金融行业的决策支持系统(DSS)中数据仓库的构建技术，针对金融行业决策支持系统中数据来源不统一、基础数据量大、数据关系复杂等特点，充分考虑系统的需求，提出了构建数据仓库的策略与方法，并且论述了具体的实现技术。     

面向园区微网的“源—网—荷—储”一体化运营方案设计

针对园区微网运营缺乏成熟的运营模式，构建了一套“源—网—荷—储”一体化的运营方案。硬件架构包括物理层、信息层和应用层。在物理层中设置源侧、网侧、荷侧和储侧，形成“供—需—储”自平衡体模式，提高了能源应用能力。还构建了MMHC算法模型，提高了微网系统中储能管理能力。试验表明，所提出的方法分析准确率高，误差低，为微网的“源—网—荷—储”一体化运营提高新思路。     

复杂适应系统与分布式卫星系统自主运行

以复杂适应系统理论为指导，探讨了基于Agent技术实现分布式卫星系统（DSS）自主运行的研究方法和主要步骤。目前国内外关于DSS自主运行技术的研究尚处于起步阶段，缺乏系统的理论指导。该文试图运用复杂适应系统（CAS）理论的思想和方法来指导DSS自主运行技术的研究，并以此扩展CAS理论的应用领域。首先介绍CAS理论的基本概念和核心思想，然后分析自主运行DSS的控制需求和特征，指出CAS理论用于指导DSS自主运行的必要性和可行性，并给出基于Agent实现DSS自主运行的整体框架。     

应用遗传算法的DSS模型设计研究

在DSS模型设计中，采用遗传程序设计可以更灵活地处理遗传算法中的表示问题。本文通过讨论遗传算法的特性，DSS模型库的特点而研究了DSS模型遗传程序设计的方法。     

《决策支持系统基础》

<正> 由美国著名信息系统专家A.B.Whiston等人撰写的《决策支持系统基础》一书(“Foundations of Decision Suppurt System”) 最近已由福建科技出版社出版发行。该书由浅入深地介绍了决策支持系统(DSS)的理论、方法和技术。全书共有五篇,作者从信息处理、决策制定和决策之间的关系为出发点,提出了一种适合各式各样决策的一般DSS结构。基于这一结构,作者详细介绍了实现DSS的数据库方法和知识工程方法,以及如何将两种方法结合使用的途径。书中还列举了许多DSS实例。     

基于数据仓库的OLAP在DSS中的应用研究

以数据仓库为基础的在线联机分析处理(OLAP)技术是决策支持系统(DSS)中一种新的决策分析方法。该文从DSS的实际需求出发,分析了数据仓库的特征和结构模型,研究了OLAP的特征和体系结构及其实现决策分析的过程,最后给出了应用实例,并探讨了完善DSS结构的研究方向。     

DSS/SINS组合导航实时滤波仿真

北斗双星定位系统的定位原理决定了其存在导航定位实时性较差的缺点。为了解决双星定位实时性差的问题，提出了一种新的北斗双星／SINS组合导航实时滤波方法，即对双星定位的静态误差进行建模，将静态误差模型作为其动态误差的残差模型与双星定位时间延迟随机常数一起扩充为组合导航滤波器的状态变量，然后对北斗双星／SINS组合导航系统进行状态估计的滤波方法。通过计算机仿真，结果表明该实时滤波方法能够更好地解决北斗双星／SINS组合导航在实际工程应用中定位实时性较差的缺点，从而提高了组合系统的导航精度，对北斗双星／SINS组合导航系统的实际应用有重要的参考价值。     

Beyond spreadsheets: tools for building decision support systems

The complexity and long development time inherent in building decision support systems has thus far prevented their wide use. A new class of tools, DSS generators, seeks to cut the lead time between development and deployment. DSS generators provide tools that make it easier and faster to develop models, data, and user interfaces that are customized to the application's requirements. Using a DSS generator reduces DSS development to a decision analysis task-which requires expertise in decision analysis and mathematical modeling-rather than a programming task. DSS generators are crucial to the success of DSSs in practice. We describe the state of the art in DSS generator software, specifically in the realm of decision analysis methods. Decision analysis techniques account for the uncertain, dynamic, and multicriteria aspects of decisions. Essentially, they aid the evaluation of alternatives in the face of trade-offs. Well known decision analysis methods include decision trees and influence diagrams. We briefly describe the features of 11 commercially available DSS generators that specialize in decision analysis. Although not a comprehensive, complete analysis of these tools, the article clarifies the idea of DSS generators as DSS development environments and presents an overview of the progress in this area     

关于决策支持系统的结构与进化

本文在总结作者开发决策支持系统的实践经验的基础上，从ＤＳＳ的结构分析入手，探讨了ＤＳＳ的进化问题，首先通过软件开发方式，程序设计风范，人工智能道路和系统科学发展等方面的深入剖析，指出了进化能力的强弱是ＤＳＳ成败的关键。其次展开了关于ＤＳＳ结构的研究，提出了ＤＳＳ的外延结构和内涵结构的新概念并进行了比较。随后讨论了ＤＳＳ的进化问题，分析了传统的第一代决策支持系统存在的缺陷，阐述了第二代和第三代决策支     

A Decision Support System for a small scale industry in a developing country

This paper describes the design and development of a Decision Support System (DSS) for a small scale manufacturing company in a developing country. The DSS provides a solution for an integrated problem of planning, shopfloor scheduling, and control. The DSS system accepts the demand data with priorities, then uses the information from the imbedded data base system regarding product structure, production process, available resources with the status, and inventory. This in turn is used by the imbedded models to solve planning and scheduling problems, and provide solutions containing job order release, shopfloor scheduling and material requirement report. What if analysis feature provided by DSS allows the managers to incorporate their knowledge and experience to improve the quality of the solution by evaluating different scenarios presented by the manager. The laboratory equipment manufactured by the company is made to order. Product information regarding twenty-two high demand items is incorporated into the data base system, and the scheduling problem is solved for these items. The jobshop is a mixed shop problem containing a flow shop, an open shop, and a flow shop. A heuristic method used for solving this problem is presented.     

粗糙集在销售决策系统中的应用

在销售决策支持系统中,存在着大量的信息和很多不确定的因素,这使得做出科学合理的决策变得很困难。粗糙集理论是处理不确定性知识与不完整数据的有效工具,因此可以根据粗糙集理论通过分析推理找出销售数据中存在的有用的知识。依据粗糙集理论实现了一种对销售决策表知识简化的方法,采用粗集理论处理大量销售信息,从中提取有用规则,通过分析和推理产生最小决策规则。通过实例分析,验证了粗糙集理论与销售决策支持系统相结合方法的可行性。该方法有效地解决了智能销售决策支持系统中决策规则的获取与理解等问题。     

Impact of design methods on decision support systems success: An empirical assessment

Many of the Decision Support Systems (DSS) developed and implemented in the last decade or so, have not been used or are only used for mundane report generation rather than for direct support of strategic planning. These failures can be attributed to the fact that existing DSS design methods (representation-based, evolutive, and adaptive) have never been evaluated with respect to their success. Thus, the designer had no way of knowing what design method to employ in developing an effective DSS.This paper investigated the relationship between the selection of a DSS design method and its ultimate success. DSS success was measured through DSS usage, user satisfaction, and user attitudes and perceptions criteria. The data utilized was collected from individuals responsible for designing and evaluating DSS, specifically the managers, intermediaries, and designers. In terms of the DSS usage and user satisfaction criteria, all three groups rated the evolutive design method superior, followed by the representation-based and adaptive methods. Using the DSS attitudes and perceptions criteria, the designer group rated the evolutive method best, followed by the representation-based, and adaptive methods. The ratings by the managers and intermediaries were rather mixed. Each design method did better in some success criteria than in others.     

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.     

An adaptive memory programming method for risk logistics operations

This paper presents a decision support system (DSS) that enables logistics planners of a well-known hank to design intra-city safe delivery routes, using an intelligent metaheuristic method and exploiting risk methodologies and spatial data information. The DSS routes minimize the probability of successful vehicle robbery at a certain point of the road network and satisfy all operational constraints of the distribution problem examined. The proposed DSS was implemented to an actual banking environment and the results obtained by this real-life application are reported.