An appropriateness framework for the Dutch Meuse decision support system

Models are essential in a decision support system for river basin management. In a decision support system for integrated planning and management, the use of appropriate models is important to avoid models being either too simple or too complex. In this paper, appropriate models refer to models that are good-enough-but-not-more-than-that to obtain an acceptable ranking of river engineering measures under uncertainty. A systematic approach called ‘appropriateness framework’ is proposed to determine appropriate models that can be used in a decision support system. The approach is applied to a decision support system for the Dutch Meuse River. One important component of this decision support system, flood safety, is used in this paper to demonstrate how this approach works. The results show that the approach is very useful in helping to determine appropriate models. Potential applications of the approach in other decision support systems are discussed. The approach presented in this paper is designed as a tool to stimulate the communication between decision makers and modelers and to promote the use of models in decision-making for river basin management.     

A framework for applying ethics-by-design to decision support systems for emergency management

The development and utilisation of new information and communication technologies presents opportunities and risks, which bring ethical issues to the forefront. Any attempt to minimise the potential negative consequences to individuals, organisations and society resulting from the use of these technologies is challenging. In order to address these challenges, this paper presents an ethics-by-design approach that has been developed and implemented in the context of Decision Supports Systems for Emergency Management. Such systems help manage large and cross-border disasters by supporting decision makers to respond on emergencies in a reasonable way by taking follow-up actions into account. The approach taken in this paper specifically provides means to support the ethical dimensions of these decisions. Actions taken during disasters can have ramifications that persist long after a disaster has passed. The ethics-by-design approach presented here not only informs the design of systems, but also considers the role and training of the decision makers in the design process. The paper builds on the literature on ethics in information systems and makes a contribution to theory by providing a framework to ensure ethical considerations are embedded into the design of systems.     

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.     

应对化学袭击的应急决策支持系统流程设计

论述了目前复杂国际环境下加强地铁安全的必要性和重要性,调研了政府及相关部门在应急准备方面所做的工作.认为及时有效的应急响应,不仅需要训练有素的人员,先进的设备,还需要高效的应急决策支持系统提供辅助支持.分析了化学恐怖袭击时相关部门和人员决策和执行过程,探讨了地铁这一类特殊环境下应对化学恐怖袭击的应急决策支持系统的功能要素和总体框架.为消防和医院等救援部门完善和快速选择恰当的应急预案、及时有效地实施救治提供依据.     

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．     

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。     

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 optimization-based decision support system for ship scheduling

The bulk carriers in the world merchant fleet typically operate full between a loading and discharging port, then run empty until they reach the next loading port. The shipping rates of bulk trades are set on supply/demand bases and fluctuate considerably. Thus the proper scheduling of ships in bulk trade has the great potential of improving the owner's profit and economic performance of shipping. This paper considers an optimization-based Decision Support System for ship scheduling. The typical optimization models for scheduling the ships are briefly reviewed and classified by the underlying idea. Then a prototype MoDiSS(Model-based SS in Ship Scheduling) which is based on a set-packing model has been developed on PC base with proper GUI. The performance of the system has been tested and examined using various ship scheduling scenarios and thereby the effectiveness of the system is validated satisfactorily.     

FireGrid: An e-infrastructure for next-generation emergency response support

The FireGrid project aims to harness the potential of advanced forms of computation to support the response to large-scale emergencies (with an initial focus on the response to fires in the built environment). Computational models of physical phenomena are developed, and then deployed and computed on High Performance Computing resources to infer incident conditions by assimilating live sensor data from an emergency in real time—or, in the case of predictive models, faster-than-real time. The results of these models are then interpreted by a knowledge-based reasoning scheme to provide decision support information in appropriate terms for the emergency responder. These models are accessed over a Grid from an agent-based system, of which the human responders form an integral part. This paper proposes a novel FireGrid architecture, and describes the rationale behind this architecture and the research results of its application to a large-scale fire experiment.     

A conceptual framework for society-oriented decision support

Inspired by the operation of human social organisation, this paper presents a new architecture—a pyramid-committee—for developing society-oriented intelligence, whose structure imitates the organisation of human society in its decision making. The system takes a pyramid-like hierarchical structure with links in the pyramid forming a semi-lattice, which relate not only to nodes in the same layer, but also to others in different layers. The output of the system is a result of the negotiation and balancing of different interests. For such a system to function, the main difficulties concern the complicated relationships between different factors or agents. Focussing on the airport environment audit, we discuss the development of a model framework and the role of neural networks.     

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.     

综合决策系统框架及其在舰船电力系统的应用

建立了舰船综合决策支持系统框架,该框架在传统的模型驱动体系结构基础上,针对决策目标,从建模优化和算法独立的角度对模型利用方法进行细分,并通过解析库的建立引入了统计分析方法,强化了数据挖掘在非结构性问题决策中的作用.将该框架应用于舰船电力系统故障后重构问题的决策以验证其有效性.算例测试结果表明,该框架下建立的决策系统能够综合多种效用函数和状态参数,有效优化了解空间,得出的电力故障恢复方案更加符合实际需求.     

An ontology-driven decision support system for land delivery in Zambia

Land is increasingly becoming important as the global economic crisis and climate change impacts continue to grow. This is mirrored in Zambia where the management of land has become very critical, prompting urgent government intervention/regulatory measures in the form of land reform. However, lack of efficient communication mechanisms inhibits the success of these efforts as officials are unable to make efficient land delivery decisions. This paper investigates the extent to which Semantic Web technology, an emerging communication technology, can be used in developing decision support systems that can facilitate the Zambian land delivery process.     

An ontology-based fuzzy decision support system for multiple sclerosis

The use of Magnetic Resonance (MR) as a supporting tool in the diagnosis and monitoring of multiple sclerosis (MS) and in the assessment of treatment effects requires the accurate determination of cerebral white matter lesion (WML) volumes. In order to automatically support neuroradiologists in the classification of WMLs, an ontology-based fuzzy decision support system (DSS) has been devised and implemented. The DSS encodes high-level, specialized medical knowledge in terms of ontologies and fuzzy rules and applies this knowledge in conjunction with a fuzzy inference engine to classify WMLs and to obtain a measure of their volumes. The performance of the DSS has been quantitatively evaluated on 120 patients affected by MS. Specifically, binary classification results have been first obtained by applying thresholds on fuzzy outputs and then evaluated, by means of ROC curves, in terms of trade-off between sensitivity and specificity. Similarity measures of WMLs have been also computed for a further quantitative analysis. Moreover, a statistical analysis has been carried out for appraising the DSS influence on the diagnostic tasks of physicians. The evaluation has shown that the DSS offers an innovative and valuable way to perform automated WML classification in real clinical settings.     

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.     

An interpretability security framework for intelligent decision support systems based on saliency map

International Journal of Information Security - Benefiting from the high-speed transmission and super-low latency, the Fifth Generation (5G) networks are playing an important role in contemporary...     

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 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 evolutionary algorithm-based decision support system for managing flexible manufacturing

The high investment cost of flexible manufacturing systems (FMS) requires their management to be effective and efficient. The effectiveness in managing FMSs includes addressing machine loading, scheduling parts and dispatching vehicles and the quality of the solution. Therefore the problem is inevitably multi-criteria, and decision maker's judgement may contribute to the quality of the solution and the systems's performance. On the other hand, each of these problems of FMS is hard to optimize due to the large and discrete solution spaces (NP-hard). The FMS manager must address each of these problems hierarchically (separately) or simultaneously (aggregately) in a limited time. The efficiency of the management is related to the response time.

Here we propose a decision support system that utilizes an evolutionary algorithm (EA) with a memory of “good” past experiments as the solution engine. Therefore, even in the absence of an expert decision maker the performance of the solution engine and/or the quality of the solutions are maintained.

The experiences of the decision maker(s) are collected in a database (i.e., memory-base) that contains problem characteristics, the modeling parameters of the evolutionary program, and the quality of the solution. The solution engine in the decision support system utilizes the information contained in the memory-base in solving the current problem. The initial population is created based on a memory-based seeding algorithm that incorporates information extracted from the quality solutions available in the database. Therefore, the performance of the engine is designed to improve following each use gradually. The comparisons obtained over a set of randomly generated test problems indicate that EAs with the proposed memory-based seeding perform well. Consequently, the proposed DSS improves not only the effectiveness (better solution) but also the efficiency (shorter response time) of the decision maker(s).     

基于电子决策剧场的城市管理决策支持系统体系架构研究

智慧城市是一个复杂的巨系统,在智慧城市管理中存在着很多的公共决策问题。针对决策过程中要解决的两大困难,一是要在城市海量信息中快速获取与决策问题相关的有价值信息,二是要降低实现群决策的时间和经济成本。提出了决策支持综合集成研讨厅的逻辑结构和基于电子决策剧场解决城市公共决策问题的方法;设计了基于电子决策剧场的城市管理决策支持系统体系架构,并给出了具体的应用流程。关键词：