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 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.     

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.     

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.     

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.     

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.     

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 adaptive stock index trading decision support system

Predicting the direction and movement of stock index prices is difficult, often leading to excessive trading, transaction costs, and missed opportunities. Often traders need a systematic method to not only spot trading opportunities, but to also provide a consistent approach, thereby minimizing trading errors and costs. While mechanical trading systems exist, they are usually designed for a specific stock, stock index, or other financial asset, and are often highly dependent on preselected inputs and model parameters that are expected to continue providing trading information well after the initial training or back-tested model development period. The following research leads to a detailed trading model that provides a more effective and intelligent way for recognizing trading signals and assisting investors with trading decisions by utilizing a system that adapts both the inputs and the prediction model based on the desired output. To illustrate the adaptive approach, multiple inputs and modeling techniques are utilized, including neural networks, particle swarm optimization, and denoising. Simulations with stock indexes illustrate how traders can generate higher returns using the developed adaptive decision support system model. The benefits of adding adaptive and intelligent decision making to forecasts are also discussed.     

广域组织内开放决策支持网格框架

针对政府机构和企业缩减规模的发展趋势,为地理上分布的管理人员进行更高效的跨应用领域决策支持提出一个5层决策支持框架,重点实现组织决策支持（Organization Decision Support,ODS）、提高决策质量,并提供一个公共操作环境以使组织在决策制定的整个生命周期中有效地进行信息协作．该框架以决策任务为主导,扩展传统的ODS框架,把不同的资源规范到一体的参考模型中,引入更多的与决策支持有关的协作模型,可为组织的辅助决策系统建设提供参考．     

An autonomous decision support system for manganese forecasting in subtropical water reservoirs

Manganese monitoring and removal is essential for water utilities in order to avoid supplying discoloured water to consumers. Traditional manganese monitoring in water reservoirs consists of costly and time-consuming manual lake samplings and laboratory analysis. However, vertical profiling systems can automatically collect and remotely transfer a range of physical parameters that affect the manganese cycle. In this study, a manganese prediction model was developed, based on the profiler's historical data and weather forecasts. The model effectively forecasted seven-day ahead manganese concentrations in the epilimnion of Advancetown Lake (Queensland, Australia). The manganese forecasting model was then operationalised into an automatically updated decision support system with a user-friendly graphical interface that is easily accessible and interpretable by water treatment plant operators. The developed tool resulted in a reduction in traditional expensive monitoring while ensuring proactive water treatment management.     

An attitude-driven web consensus support system for heterogeneous group decision making

Consensus reaching processes are applied in group decision making problems to reach a mutual agreement among a group of decision makers before making a common decision. Different consensus models have been developed to facilitate consensus reaching processes. However, new trends bring diverse challenges in group decision making, such as the modelling of different types of information and of large groups of decision makers, together with their attitude to achieve agreements. These challenges require the capacity to deal with heterogenous frameworks, and the automation of consensus reaching processes by means of consensus support systems. In this paper, we propose a consensus model in which decision makers can express their opinions by using different types of information, capable of dealing with large groups of decision makers. The model incorporates the management of the group’s attitude towards consensus by means of an extension of OWA aggregation operators aimed to optimize the overall consensus process. Eventually, a novel Web-based consensus support system that automates the proposed consensus model is presented.     

Fuzzy decision support system for fertilizer

Fuzzy geographic information systems is a newly emerging field of computational intelligence. It combines fuzzy logic with spatial context. Most of the natural phenomena are fuzzy in nature. They show a degree of uncertainty or vagueness in their extent and attribute, which cannot be expressed by a crisp value. Agriculture is one of the fields of the spatial domain that needs to be described in fuzzy terms. Fertilizer is a key input for the agriculture sector. In this article, the spatial surfaces of fertilizers are developed for the wheat crop using a fuzzy decision support system. The algorithm of our system takes soil nutrients and cropping time as input, applies fuzzy logic on the input values, defuzzifies the fuzzy output to crisp value, and generates a fertilizer surface. The resultant output surface of fertilizer describes the amount of fertilizer needed to cultivate a specific crop in a specified area. The complexity of our algorithm is \(O(mnr)\) , where \(m\) is the height of the raster, \(n\) is the width of the raster, and \(r\) is the number of expert rules.     

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．