CZ-CIMS设计与实现

该CIMS系统是典型的流程型CIMS系统,它实现了决策支持分系统、生产指挥分系统、过程控制分系统、质量保证分系统、营销管理分系统和综合办公管理分系统等六大分系统的有效集成。该系统采用B/S结构,实现企业物流、信息流、资金流三流合一,建立了开放性的现代化集成系统。     

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.     

TPC-DS性能测试工具的实现

阐述了新一代面向决策支持的数据库性能测试基准TPC-DS的数据模型、业务模型、执行模式和度量方法,设计了一个支持不同数据库管理系统(DBMS)性能对比测评的TPC-DS测试框架,阐述了配置文件、查询执行控制、数据维护机制等关键实现技术。最后通过对任务配置和语法配置的实践,验证了工具对不同DBMS、不同优化配置的对比测试可用性。     

Using an integrated model learning system to construct the model base of a decision support system

The Model Base Management System (MBMS) in a Decision Support System (DSS) has become increasingly important in handling complicated decision problems. Traditionally, models are retrieved from the human experts. This approach has the disadvantages of low productivity and being subjective by different individuals. Although recent research projects include how to apply Artificial Intelligence approaches to automatic model retrieval, none of them provides an efficient and effective way to produce large-scale complicated models. In this article, an Integrated Model Learning System is introduced to learn new models from model instances. This system basically uses the Multiple Instance Explanation Based Generalization (miEBG) approach which is a modification of the Multiple Explanation Based Generalization (mEBG) approach to explain and generalize model instances by the Domain Theory. Different from other machine learning approaches, this approach takes advantages of using the Domain Theory to learn multiple explanation trees from instances, and then combines all trees to form a complete explanation tree which will be generalized into a useful model. In general, this approach provides the Model Base Management System an automatic way to retrieve new and more complete models from related instances in a self-learning fashion.     

Corporate dashboards for integrated business and engineering decisions in oil refineries: An agent-based approach

It is generally very challenging for an oil refinery to make integrated decisions encompassing multiple functions based on a traditional Decision Support System (DSS), given the complexity and interactions of various decisions. To overcome this limitation, we propose an integrated DSS framework by combining both business and engineering systems with a dashboard. The dashboard serves as a human-computer interface and allows a decision maker to adjust decision variables and exchange information with the DSS. The proposed framework provides a two-stage decision making mechanism based on optimization and agent-based models. Under the proposed DSS, the decision maker decides on the values of a subset of decision variables. These values, or the first-stage decision, are forwarded through the dashboard to the DSS. For the given set of first-stage decision variables, a multi-objective robust optimization problem, based on an integrated business and engineering simulation model, is solved to obtain the values for a set of second-stage decision variables. The two-stage decision making process iterates until a convergence is achieved. A simple oil refinery case study with an example dashboard demonstrates the applicability of the integrated DSS.     

决策支持系统与地理信息系统的集成化研究

通过村庄布局优化决策支持系统案例,着重讨论Ｔ ＧＩＳ与 ＤＳＳ的系统集成,介绍了实现 ＤＳＳ与 ＧＩＳ集成的技术,即ＧＩＳ采用独立开发的电子地图引擎,采用与ＤＳＳ相一致的数据管理工具,在较低的层面上实现统一的数据结构和规范的数据交互,从而实现地理信息库与数据库和模型库的有机链接,实现在地图上村庄信息的显示和查询,以及村庄合并搬迁后在地图上的动态变化,使用户的决策活动更直观方便。     

商业智能决策支持系统(BIDSS)

文章将人工智能(AI)、决策支持系统(DSS)、数据挖掘(DM)、WEB等技术与传统的商场计算机管理系统结合起来,建立了商业智能决策支持系统的模型,并给出了实现商业智能决策支持系统的关键技术。     

基于面向对象模型库的商业决策支持系统

目前,管理信息系统(MIS)已经在我国商业企业中得到了广泛的应用。但目前商业中的管理信息系统仍然还停留在基本事务处理的阶段,为决策者提供决策支持的功能比较弱。解决这一问题的途径是设计一套基于MIS的商业决策支持系统。决策支持系统是利用各种数据、信息、知识,特别是模型技术,辅助各级决策者解决结构化、半结构化决策问题的人机交互系统。该系统采用了模型/方法库、数据库、会话控制系统三模块的总体架构。模型/方法库的设计和管理是该系统的核心和难点所在。该文提出了利用面向对象技术实现模型/方法库的构造,参考数据库管理模式来管理模型库。预测是决策的基础。由于不同的模型针对不同的商业经营数据─主要表现为离散随机型的时间序列值─的预测效果不同,文章提出了一种思路,通过比较各预测模型的预测误差,选择出最优的预测模型,解决了多模型预测的自适应问题。该文所提出的模型的定义方法、模型/方法库的构造思路,基本上是一种通用的模型设计思路,对于其它决策支持系统的设计也有一定的参考作用。     

决策过程与决策支持系统关系的新视角

该文以新的视角来研究决策过程和决策支持系统。首先,以全新的观点阐释了决策过程和决策支持系统的结构,并绘制出相应的结构图;其次,以此为基础,绘制出了二者之间的层次结构模型图,揭示了决策支持系统和决策过程的内在联系。     

A software architecture and framework for Web-based distributed Decision Support Systems

This paper presents an integrated method to help design and implement a Web-based Decision Support Systems (DSS) in a distributed environment. First, a layered software architecture is presented to assist in the design of a Web-based DSS. The layered software architecture can provide a formal and hierarchical view of the Web-based DSS at the design stage. Next, a component-based framework is presented to implement the Web-based DSS in a distributed environment. Finally, an instance of the layered software architecture and 3CoFramework applied to the Web-based National Agricultural Decision Support System (NADSS) is presented.     

Flexible decision support in dynamic inter-organisational networks

An effective Decision Support System (DSS) should help its users improve decision making in complex, information-rich environments. We present a feature gap analysis that shows that current decision support technologies lack important qualities for a new generation of agile business models that require easy, temporary integration across organisational boundaries. We enumerate these qualities as DSS Desiderata, properties that can contribute both effectiveness and flexibility to users in such environments. To address this gap, we describe a new design approach that enables users to compose decision behaviours from separate, configurable components, and allows dynamic construction of analysis and modelling tools from small, single-purpose evaluator services. The result is what we call an ‘evaluator service network’ that can easily be configured to test hypotheses and analyse the impact of various choices for elements of decision processes. We have implemented and tested this design in an interactive version of the MinneTAC trading agent, an agent designed for the Trading Agent Competition for Supply Chain Management.     

Local Area Management and Planning (LAMP) in India

To assist decentralised planning, the Department of Science and Technology, Government of India has taken the initiative to develop a computer-based spatial information system for planning and management of the natural resources at the district and sub-district level. At present ten district level database centres called Natural Resources Data Management System (NRDMS) have been functioning in different geo-environments in India.
The present paper discusses the experience of the Centre for Applied Systems Analysis in Development (CASAD). CASAD is involved in managing the NRDMS database centre at Bankura district and was associated with the development of DSS models in Kheda district. Finally, a few case studies on the use of Decision Support Systems (DSS) for decentralised decision making at the district level are discussed.     

烟草业务联机分析处理系统的实现

数据库技术的广泛应用以及数据仓库技术的出现为决策支持系统提供了新的发展方向。联机分析(onlineanalyticalprocessing,简称OLAP)正是在数据仓库的基础上发展起来的一门崭新的决策技术。文章结合某市烟草决策支持系统,介绍了基于联机分析处理技术的烟草数据分析系统的设计思路与实现方法,并对其中关键环节进行了较为详细的探讨与阐述,为联机分析处理技术的实用化提供了可借鉴的成功经验。     

Experience of model integration and Pareto frontier visualization in the search for preferable water quality strategies

A real-life application of a new approach to integrated assessment and screening of water quality improvement strategies in large river basins is presented. The approach is based on the integration of diverse data and mathematical models as well as on the application of interactive visualization of the Pareto frontier. The case study water quality planning in the Oka River, the Volga River basin, is presented within the framework of a DSS for screening water quality planning strategies. The Decision Support System (DSS) was commissioned by the Russian Federal Ministry for Natural Resources within the Federal programme “Revival of the Volga River”.     

工作流管理系统的动态路由的设计与实现

探讨了在工作流管理系统中实现动态路由的方法 ,提出了使用 XML 语言定义路由规则 ,路由的注册、发布与查询 ,节点与引擎之间松散的路由连接等技术方案 .我们实现了基于这种方案的工作流管理系统原形 ,并在三峡梯级AGC系统取得了成功的运用     

GFKD—DSS决策支持系统开发工具

GFKD-DSS系统是一个决策支持系统开发工具.它由两大部分组成:管理系统和运行控制系统.管理系统提供DSS管理语言,实现对模型库的管理、模型文件的管理和对数据库的使用.运行控制系统提供DSS核心语言,该语言具有数值计算、数据处理,模型控制、多个模型的组合等多种功能的综合能力.利用本系统能生成国民经济、军事指挥中各种半结构化或非结构化决策问题的决策支持系统.     

An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks

In this paper, we propose a novel Intrusion Detection System (IDS) architecture utilizing both anomaly and misuse detection approaches. This hybrid Intrusion Detection System architecture consists of an anomaly detection module, a misuse detection module and a decision support system combining the results of these two detection modules. The proposed anomaly detection module uses a Self-Organizing Map (SOM) structure to model normal behavior. Deviation from the normal behavior is classified as an attack. The proposed misuse detection module uses J.48 decision tree algorithm to classify various types of attacks. The principle interest of this work is to benchmark the performance of the proposed hybrid IDS architecture by using KDD Cup 99 Data Set, the benchmark dataset used by IDS researchers. A rule-based Decision Support System (DSS) is also developed for interpreting the results of both anomaly and misuse detection modules. Simulation results of both anomaly and misuse detection modules based on the KDD 99 Data Set are given. It is observed that the proposed hybrid approach gives better performance over individual approaches.     

基于KW、MW及DW的决策支持系统架构研究

SDSS是较为先进的决策支持系统，但由于其模型库中的模型固定不变，因此在实际应用中具有一定的局限性。提出了集成数据仓库DW、知识仓库KW和模型仓库MW作为底部架构的体系结构，能有效解决这一问题。该架构简化了模型获得和编码任务，增强了决策的有效性和智能性，提高了决策效率。     

A structured modeling based methodology to design decision support systems

Many Decision Support Systems (DSS) support the decision making process through the use of mathematical models and data. DSS design involves modeling data as well as mathematical relationships in a domain. The process of model formulation and subsequent integration of model with data in a DSS is a complex and ill-structured process. This paper proposes a methodology based on Structured Modeling (SM), originally introduced by Geoffrion together with the modeling language SML, to model and design the DSS. The methodology includes rigorous and step by step procedures to design and integrate data and modelbases. The main contribution of our approach lies in the integration of research in database design, and mathematical model formulation within the structured modeling framework. The resultant procedures can be easily automated and taught to students in DSS courses. The motivation for our research stemmed from our constant frustrations in teaching DSS courses over the last five years. In the last two years, when we used our methodology, the performance of the students improved significantly. The average score in the DSS project went up to 85 from 60. Our positive experience in using our methodology in classes over the past two years suggests that the methodology imposes structure into the analysis of decision problems, and as a result students produce better DSS designs for classroom cases.     

虚拟产品设计方案神经网络决策模型研究

虚拟原型逼真设计作为虚拟产品开发研究的一个方面,是近几年发展起来的新技术,主要研究虚拟环境下的产品建模问题以及基于仿真的集成产品和过程设计问题。生命周期虚拟产品设计方案评价模型是虚拟原型逼真设计模型实现的重要模块之一,论文在设计方案多目标多级模糊综合决策模型的基础上,研究并建立了设计方案ANN多目标决策模型,该模型已应用于仪表新产品开发决策支持系统中。