An integrated framework for group decision support systems design

Proposed approaches for the development of Group Decision Support Systems (gdss) address behavioral and technical aspects of these systems. However, these approaches generally address only one of these aspects at a time. This paper reviews these approaches and suggests a framework for developing gdss based on an integrated perspective. This proposed framework is comprehensive and integrative as it combines the behavioral characteristics of group decision making with the technical specifications that drive gdss. Software design and future research issues are discussed.     

A framework for decision support systems evaluation

In this paper, we present a framework for the Decision Support Systems evaluation problem. Using the Gorry-Scott Morton's framework for information systems, we develop several evaluation methods that structure the evaluation process. The framework determines the best methods of evaluation that are suitable to the characteristics of the Decision Support System concerned. Finally, we use the framework to evaluate two widely used Decision Support Systems.     

A framework for systems analysis for decision support systems

Comprehensive and elaborate systems analysis techniques have been developed in the past of routine and operational information systems. Developing support systems for organizational decision-making requires new tools and methodologies. We present a new framework for data collection and decision analysis which is useful for developing decision support systems. This task analysis methodology encompasses (1) event analysis, (2) participant analysis, and (3) decision content analysis. With a proper coding manual, it provides a framework for collecting relevant and detailed information required for decision support design and implementation. Further research is suggested for application and evaluation of the methodology in real-life DSS environments.     

An automata-theoretic framework for intelligent systems

A theoretical framework for the analysis and synthesis of intelligent systems is presented. The basic models of automata theory and adaptive systems are highlighted, then extended and interpreted in the context of intelligent system design. In particular, the basic models are generalized to intelligent systems incorporating self-learning behavior. The utility of this approach is demonstrated by its use as a rigorous basis for (1) the discussion of information minimization in automatic systems, (2) the formal structure of adaptive systems and (3) implications for a general theory of intelligent systems.     

面向虚拟采办的智能决策支持系统概念框架

提出一种面向虚拟采办全寿命周期、全系统、全方位决策的智能决策支持系统SBA—IDSS概念框架．作为真实世界采办最终需求的抽象描述,它属于与实现无关的规范性模型体系,由它定义应用领域、用户概念和环境特征．同时它是数字世界中拟实现的初始工程模型,包括与实现无关的设计可行性模型、规划模型及功能顶层分解．该框架支持系统的自组织、自适应智能行为,预期可按需组成模型与仿真、文件、知识、通信及数据驱动的各类实用决策支持系统．该框架通过一项SBA实例的验证,得到可用性的正面评价．     

A general framework for time-aware decision support systems

In this paper we present a general framework for time-aware decision support systems. The framework uses the state-of-the-art tOWL language for the representation of temporal knowledge and enables temporal reasoning over the information that is represented in a knowledge base. Our approach uses state-of-the-art Semantic Web technology for handling temporal data. Through such an approach, the designer of a system can focus on the application intelligence rather than enforcing/checking data related restrictions manually. Also, there is an increased support for reuse of temporal reasoning tools across applications. We illustrate the applicability of our framework by building a market recommendations aggregation system. This system automatically collects market recommendations from online sources and, based on the past performance of the analysts that issued a recommendation, generates an aggregated recommendation in the form of a buy, hold, or sell advice. We illustrate the flexibility of our proposed system by implementing multiple methods for the aggregation of market recommendations.     

A decision support framework for security resource allocation under ambiguity

There has been increasing interest in using Stackelberg game (known as a security game) to allocate limited security resources against different attacker types with a specific probability distribution. However, real problems of this kind often face ambiguous information, such as imprecise, unreliable and absent payoffs, and ambiguous assignments of these payoffs. To this end, based on decision theory and the Dempster–Shafer theory of evidence, this paper proposes a novel framework that can handle these common types of ambiguity. More specifically, this paper deploys the underlying principles of existing rules from decision theory, as a way to characterise different attitudes to ambiguity, during the transformation of ambiguous payoffs into point‐valued payoffs. Hence, our framework holds some good properties: (i) it subsumes traditional security games without ambiguous payoffs, (ii) a uniform margin of error will not affect the results and (iii) the influence of complete ignorance can be minimised. Also, our framework is evaluated by using nine different transformation rules, under various conditions and constraints, against 73,000 randomly generated games (a first comprehensive empirical evaluation to date). The evaluation reveals the benefits of each transformation rule and confirms that different rules can model individuals' different attitudes to ambiguity.     

基于Web的决策支持系统界面开发的一种面向对象框架

随着Internet/Intranet在现代企业中的广泛应用，基于Internet/Intranet的决策支持系统已成为一个亟待研究的新领域。许多学者已经对如何把面向对象的编程思想运用到模型管理系统和数据库管理系统中作了大量的研究，但对于界面开发方面的研究还很少。提出了针对基于Web的决策支持系统界面开发的一种面向对象的框架。与传统的方法（如HTML／CGI）相比，这个框架具有鲁棒性、可重用性、可扩展性等优点。最后给出了仿真实例。     

Fuzzy cognitive map architectures for medical decision support systems

Medical decision support systems can provide assistance in crucial clinical judgments, particularly for inexperienced medical professionals. Fuzzy cognitive maps (FCMs) is a soft computing technique for modeling complex systems, which follows an approach similar to human reasoning and the human decision-making process. FCMs can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Medical decision systems are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall clinical decision with a different degree. Thus, FCMs are suitable for medical decision support systems and appropriate FCM architectures are proposed and developed as well as the corresponding examples from two medical disciplines, i.e. speech and language pathology and obstetrics, are described.     

An intelligent decision support system for digital preservation

This paper describes a Service Oriented Architecture (SOA) based on Web services technology designed to assist cultural heritage institutions in the implementation of migration based preservation interventions. The proposed SOA delivers a recommendation service and a method to carry out complex format migrations. The recommendation service is supported by three evaluation components that assess the quality of every migration intervention in terms of its performance (Migration Broker), suitability of involved formats (Format Evaluator) and data loss (Object Evaluator). Throughout the paper the whole workflow between these three components is explained in detail as well as the most relevant tasks that are carried out internally in each of them. The proposed system is also able to produce preservation metadata that can be used by client institutions to document preservation interventions and retain objects’ authenticity. Although the primary goal of this SOA is the implementation of migration based preservation interventions, it can also be used for other purposes such as comparing file formats or evaluating the performance of conversion applications.     

An intelligent agent-based collaborative information security framework

In this paper we proposed a framework for collaborative intelligent agents in a distributed environment to execute sound security strategies for protecting information resources. First, the intelligent agent-based Duty Reliable Center (DRC) in the model uses the group decision method to determine a global information threat level. With the threat level, local agent employs the Bayes’ decision procedure to calculate the expected loss of its all-possible actions, and then chooses an action among them with the minimum expected loss to protect its information resources. The proposed framework enables an agent to choose among alternatives in an optimal fashion, taking into account the worth of acquiring prior information to reduce uncertainty. Because system operations are distributed, hackers are unlikely to wreck the whole system. Thus, it is expected to yield information security cost-effective solutions.     

A research framework for Web-based open decision support systems

With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). In this paper, we propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS and creates a uniform research framework for various decision support systems. The conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also analyze the basic functions and develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS function efficiently. Finally, an illustrative example is studied to support the proposed ideas.     

Contextual fuzzy cognitive map for decision support in geographicinformation systems

Fuzzy cognitive maps or FCMs have been shown to be useful when representing qualitative data. We have shown that these FCM structures can be used to represent quantitative and qualitative data. We illustrate this structure applied to geographic information system (GIS) applications. We illustrate the types of CFCMs we can generate using real census data, human expert knowledge, and quantitative data in the form of maps in a GIS. The goal of this system is to use objects (topographical and conceptual) and their relationships, either supplied by census data or generated by the GIS and to map them as layers in the GIS. Using fuzzy membership functions from experiments with GIS users, we can construct CFCMs for decision support. This will also have significant applications in intelligent servants that are able to assist and interact with the human user     

A Jini‐based software framework for developing distributed cooperative decision support systems

Many mission‐critical, decision‐making situations happen in dynamic, rapidly changing, and often unpredictable environments. Military, governmental, and medical contexts are examples of such situations, which can be characterized by highly decentralized, up‐to‐date data sets coming from various sources. Unlike other decision‐making tools, decision support systems (DSS) designed for such situations are challenged by the need to access this decentralized data at any time, from anywhere, under tight time constraints. This paper presents the design of a software framework for developing these kinds of distributed DSSs. The proposed Java‐based framework relies mostly on the Jini technology and its JavaSpaces service. The construction of the framework is presented with UML class diagrams, UML sequence diagrams, and additional explanations. Copyright © 2003 John Wiley & Sons, Ltd.     

面向体系虚拟采办的智能决策支持系统

为满足信息化战争形态对体系采办的需求,基于体系性能固有特征对虚拟采办的技术要求,在传统单系统虚拟采办技术基础上建立协同工程环境CEE,有效支持基于模型的系统工程MBSE．应用层新增智能决策支持系统IDSS旨在提高决策者的认知决策和群体研讨决策能力以获取初始需求定义模型,运用综合集成法与建模与仿真使能工具以优化模型构造与演化过程．IDSS既是CEE上的MBSE应用,与SBA应用共享可拓展资源层,又是SBA的支持系统,它运用构件按需组合的机制自动链接和执行工作流程而达到具体SBA问题求解的目标,并以紧致耦合和Web服务两种决策支持方式选项来适应用户需要．配合IDSS,在CEE中间件平台和资源层进行了相应的技术拓展．已实现的IDSS实用原型系统的可用性、有效性和技术优势,已通过体系采办实例得到了验证．文章最后给出了继续努力的几个方向．     

基于多Agent的决策支持系统模型研究

为了解决目前市场上许多企业推出的商务智能产品模型存在主动性差、智能性较低和系统集成困难等缺陷,利用现有的多Agent技术建立了一个商务智能系统MABIS,力图弥补现有商务智能系统存在的缺陷,减少对用户的依赖性.给出了一个基于多Agent技术的商务智能系统--MABIS及其系统架构,并分析了MABIS系统的工作流程和模型的可扩展性.介绍了实现MABIS的关键技术,分析了MABIS系统各部分的实现细节,给出了规则的描述方法以及基于规则的推理过程.     

An intelligent decision support system for management of petroleum-contaminated sites

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers.     

An intelligent control and decision approach for adaptive systems

An intelligent control and decision-making (ICD) approach that integrates expert systems technology with adaptive algorithms is presented. The controller parameters of adaptive systems can be determined using human expertise and knowledge, and they can also be adjusted based on active monitoring and identification. Decision-making, fine tuning and inexact reasoning provide the end-user and the control engineers with a natural and integrated methodology for use with intelligent control systems. Computer simulation results demonstrate the utility of the proposed technique that is an effective intelligent control and decision approach. The ICD system is implemented using a Lisp based expert system shell on an IBM PC.     

An effective database formation for decision support systems

Managers' tasks have two aspects: to monitor (control) business activities and to plan the future based upon the monitored results. Thus a decision Support System (DSS) must have two kinds of databases appropriate for its needs.A management database, i.e., one for monitoring activities, is constructed mainly from the existing operational databases. A data cube should be employed for the logical data structure of the management database so that managers can share it and access it in multiple ways.Planning databases, i.e., those for planning activities, are constructed mostly from the management database. A table form should be employed for its logical data structure so that managers will find it easy to use.The management and planning databases should be connected through DSS's system architecture [1]. This makes the operational data (indicating business activities) directly and immediately available for management decision making.We have previously presented the DSS architecture. This paper discusses the management and planning databases from the viewpoint of it.     

An environment for development of decision support systems

As decision support systems gain widespread acceptance among decision makers, the demand for such systems is accelerated. The changing nature of DSS calls for a speedy development. However, the traditional system development techniques do not support the rapid development of such systems. This paper describes an environment for development of decision support systems. This environment offers a set of automatic and semi-automatic tools through which the speedy development of a high-quality DSS is greatly facilitated.