Developing and assessing an intelligent forex rolling forecasting and trading decision support system for online e‐service

An effective foreign exchange (forex) trading decision is usually dependent on effective forex forecasting. In this study, an intelligent system framework integrating forex forecasting and trading decision is first proposed. Based on this framework, an advanced intelligent decision support system (DSS) incorporating a back‐propagation neural network (BPNN)‐based forex forecasting subsystem and Web‐based forex trading decision support subsystem is developed, which has been used to predict the directional change of daily forex rates and provide intelligent online decision support for financial institutions and individual investors. This article describes the forex forecasting and trading decision method, the system architecture, main functions, and operation of the developed DSS system. A comparative study is conducted between our developed system and others commonly used in order to assess the overall performance of the developed system. The assessment results show that our developed DSS outperforms some commonly used forex forecasting and trading decision systems and can provide intelligent e‐service for forex traders to make useful trading decisions in the forex market. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 475–499, 2007.     

Designing a robo-advisor for risk-averse,low-budget consumers

Banks have reacted much more enthusiastically to the FinTech revolution than many of their customers. Robo-advisory, automated web-based investment advisory, in particular promises many advantages for both banks and customers - but consumer adoption has been slow so far. Recent studies suggest that this might be due to a mix of low trust in banks, high expectations of transparency and general inability or unwillingness to engage with investment questions. Research in decision support and guidance shows customers’ willingness to interact with a decision support tool depends greatly on its usability. We identify requirements for robo-advisory, derive design principles and evaluate them in two iterations with a real robo-advisor in a controlled laboratory study. The evaluation results confirm the validity of our identified design principles.     

A web DSS approach to building an intelligent internet shopping mall by integrating virtual reality and avatar

This paper is concerned with designing and implementing the Internet shopping mall by using a virtual reality-driven avatar and web decision support system (Web DSS). Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and texts. However, this sort of approach results in a lower performance because possible customers cannot make accurate shopping decisions. To overcome these kinds of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and Web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of the alternatives that guarantee a sense of reality for the customers' part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make the Internet shopping-related decision making processes easier. Second, the Web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed Web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.     

A natural-disaster management DSS for Humanitarian Non-Governmental Organisations

Humanitarian Non-Governmental Organisations (NGOs) play a growing role in the response to natural disasters, but despite being largely demanded, there is no available decision support system (DSS) specifically designed to address their problem. In this paper we present a decision support system (DSS) to aid those Humanitarian NGOs concerned with the response to natural disasters. Such a DSS has been designed avoiding sophisticated methodologies that may exceed the infrastructural requirements and constraints of emergency management by NGOs. A data-based, two-level knowledge methodology which allows damage assessment of multiple disaster scenarios is presented in order to address that problem. Validation results show viability of our approach.     

Automating concept development by analogical reasoning for advanced decision aids

Compared with conventional knowledge-based decision aids, decision support systems for product concept design must support concept development at the initial stage of human decision making. To support such processes, we must implement both interactive support and automated concept development.

This paper is concerned with the latter, and proposes an automated concept development method using analogical reasoning. The features of the method are that it generates a new product similar to a given product with unique concepts and that it augments domain theory to expand the applicability of the new product.

To validate the performance of the proposed method, we have applied the method to an electric appliance domain. From our experiments, the method has developed not only well-known concepts but also some unique concepts which have not been produced.

Although the proposed method is very simple, it has a highly extensible architecture. Therefore, we conclude that the system can be used to support the initial stage of human decision making.     

企业集团分布式数据仓库及决策支持系统研究

为了构建支持企业集团决策分析的信息系统,分析了企业集团决策支持系统信息模型,给出了面向整个集团的基于分布式数据仓库的企业集团决策支持系统的体系结构;通过定义决策方案模型及决策任务模型,提出了模型驱动的企业集团决策支持系统解决方案,并给出了决策任务模型并行执行算法。应用表明,该体系结构是可行且有效的。     

面向对象的深立井凿井决策支持系统的设计

本文基于面向对象的设计思想,结合决策支持系统相关技术,通过构造面向对象的深立井施工钻眼爆破系统和凿井设备选型计算系统模型,采用面向对象技术的封装、继承和消息处理等特性,将传统的系统框架和选型规则、知识结合封装成为深立井凿井中新的对象知识库,突出规则知识表示的灵活性和框架知识表示的结构性,同时结合语义网络的特点,构建出深立井凿井决策支持系统。系统科学地实现了深立井凿井设备的选型、计算任务书和炮眼布置图的自动生成等功能,从而为深立井施工钻爆系统设计以及凿井设备选型提供新的服务载体。     

Systematic modeling and model handling for manpower planning systems

The primary purpose of this paper is to show an efficient way of handling models and model data in a decision support system, in which it is usual to consider several variants of a model. The model data primarily consist of model-defining data, but the same approach may be used for the generated results as well. By efficient handling is meant the handling by the computer as well as by the user. For the user it is particularly important that new models can be conveniently defined as variants of existing models. The approach is introduced within the context of a decision support system for manpower planning based on Markov models. In the mean time the same approach has been used for the implementation of other decision support systems and has been found to be more generally applicable.     

W波段微波辐射计

详细介绍了在航天863-2的支持下,开展的W波段(92 GHz)和F波段(118.75 GHz)毫米波辐射计研究,这两个频率微波辐射计的研究在国内还属首次。F波段微波辐射计正在研制过程中,已完成W波段微波辐射计的系统集成,并对系统各项指标进行了测试。     

A probabilistic reasoning-based decision support system for selection of remediation technologies for petroleum-contaminated sites

Selection of remediation technologies for petroleum-contaminated sites is difficult given the large number of technologies available and inherent uncertainties involved in the selection process. In this paper, we explore the use of an inexact algorithm for probability reasoning for dealing with the uncertainties involved in the problem. By incorporating domain knowledge as well as the stochastic uncertainty, a probabilistic rule-based decision support system (PDSS) has been developed to support the decision making process. The system has been applied to two case studies, in which the best option of remediation technology can be determined according to calculated probability values. In comparison to deterministic and fuzzy decision support systems, the PDSS can provide a recommendation together with a measure on the reliability or degree to which the recommended decision can be trusted.     

Predicting adequacy of vancomycin regimens: A learning-based classification approach to improving clinical decision making

Clinicians' drug regimen decision making is critical, particularly when involving high-alert medications. In this study, we use decision-tree induction C4.5 and a backpropagation neural network to construct decision support systems for predicting the regimen adequacy of vancomycin, a glycopeptide antimicrobial antibiotic effective for Gram-positive bacterial infections. We comparatively evaluate the respective systems using a total of 987 clinical vancomycin cases collected from a major tertiary medical center in southern Taiwan. We supplement each system using Bagging and then examine the predictive power of the extended system. Overall, our evaluation results show the overall accuracy of the decision support system based on C4.5 or the neural network to be significantly higher than that of the benchmark one-compartment pharmacokinetic model. Use of Bagging can considerably improve the effectiveness of each system across different performance measures, particularly for cases of decision classes in which the base systems (i.e., without Bagging) perform modestly. Taken together, our evaluation results seem to favor the use of Bagging to enhance the performance of decision support systems constructed using decision-tree induction C4.5.     

Incorporation of the Arden Syntax within the Reimplementation of a Closed-Loop Decision Support System

The initial implementation of a clinical decision support system, although extremely successful and popular with users, suffered from response time and operational support difficulties. As part of the redesign of the system, which uses closed-loop rules to propose laboratory and other investigations, the decision was taken to move to Arden Syntax for the expression of such rules, although in some areas the current standard was felt to be either inadequate or inelegant. Such limitations have been overcome by the development of local extensions to the Arden Syntax, which are described and where appropriate proposed as possible enhancements of the standard. The use of common UNIX tools in the creation of a compiler which converts Arden Medical Logic Modules to M (MUMPS) code is also discussed.     

A knowledge-based decision support system to analyze the debris-flow problems at Chen-Yu-Lan River, Taiwan

Decision-making for the debris-flow management involves multiple decision-makers often with concerning geomorphological and hydraulic conditions. Spatial decision support systems (SDSS) can be developed to improve our understanding of the relations among the natural and socio-economic variables to the occurrence/non-occurrence samples of debris-flow. Accordingly, the goal of this study is to development a debris-flow decision support system to manage and monitor the debris-flows in Nan-Tou County, Taiwan. The present study, more specifically, combines a spatial information system with an advanced Data Mining technique to investigate the debris-flow problem. In the first stage, our spatial information system integrates remote sensing, DEM, and aerial photos as three different resources to generate our spatial database. Each of the geomorphological and hydraulic attributes are obtained automatically through our spatial database. Then, a Data Mining classifier (hybrid model of decision tree (D.T.) + support vector machine (S.V.M.)) will be used to analyze and resolve the classification of occurrence of debris-flow. The contribution of this study has found that watershed area and NDVI (Normalized Difference Vegetation Index) are the crucial factors governing debris-flow by means of decision tree analysis. Further, the performance of prediction accuracy on testing samples through support vector machine is 73% which could be helpful for us to have better understanding of debris-flow problem.     

面向对象的决策支持系统结构建立方法研究

针对决策支持系统中传统系统结构建立方法的不足,该文采用O-S图来描述一般决策支持系统的面向对象的系统结构,提出了用O-S图建立决策支持系统的面向对象的系统结构的八个具体实现步骤这一新方法,并成功运用于王禾丘农村能源系统生态工程研究的决策支持系统开发中,缩短了开发周期,提高了决策支持系统的开发效率。     

An Australian Perspective on Research and Development Required for the Construction of Applied Legal Decision Support Systems

At the Donald Berman Laboratory for Information Technology and Law, La TrobeUniversity Australia, we have been building legal decision support systems for a dozenyears. Whilst most of our energy has been devoted to conducting research in ArtificialIntelligence and Law, over the past few years we have increasingly focused uponbuilding legal decision support systems that have a commercial focus.In this paper we discuss the evolution of our systems. We begin with a discussion ofrule-based systems and discuss the transition to hybrid rule-based/case-based systems.We next discuss how we have used machine learning in building legal decision supportsystems. Our focus on using machine learning led us to investigate the domains ofexplanation and argumentation. We conclude by discussing our current work onbuilding negotiation support systems and tools for constructing web-based legaldecision support systems.     

基于物联感知的城区内河应急决策支持系统建设

针对城区内河突发事件的事前实时预警、事中高效分析处理及事后及时反馈的应急处置需求,采用 B/S 架构,基于 Web GIS 平台设计应急决策支持系统。系统架构分为信息采集层、数据支撑层、业务应用层和用户层及信息安全体系。研究设计物联感知体系,实现水环境信息的自动监测预警和闸泵自动化远程控制;集成已有业务应用系统和数据,通过科学的数据组织形式制定应急会商专题信息展板,并结合 ArcGIS API 地图可视化方法在线直观展示各类应急信息,辅助专家进行决策判断。该系统已运用于宁波城区内河城区管理,效果良好。     

Pluralistic multi-agent decision support system: a framework and an empirical test

Recent research in decision support systems (DSSs) has focused on building active cooperative intelligent systems. Research in agent-based decision support is a promising stream in this direction. This paper proposes a framework for a pluralistic multi-agent decision support system (MADSS). The distinguishing feature of the proposed approach is its organization around human decision making process. The framework builds upon the decision support pyramid with agents organized into groups according to the phases of the problem solving model. We outline the design principles and develop architecture for MADSS. The framework is illustrated through an investment MADSS prototype. The results of the empirical test are presented.     

Investigation of decision making process: a hypermedia approach

Research in decision making has concentrated mainly on the decision outcome (choice) rather than on the process of the decision making. This pattern is primarily due to the lack of an acceptable unobtrusive tool for investigation of the decision process. Further, the lack of a consistent decision aid in empirical works has hindered the comparison of results. The purpose of this paper is to present a flexible and adaptable computer-based system for empirical examination of information processing. The main thrust of the proposed system is to provide guidelines to the restrictive/channeling approach to system design. This system can be easily modified to suit different experimental research requirements. It should support more realistic decision tasks, which often are criticized in decision experiments. Furthermore, availability of this system should encourage more research work on the process of decision making. The nature of this support system is linked to the literature, and specifications and components of the system are provided.     

Investigation of decision making process: a hypermedia approach

Research in decision making has concentrated mainly on the decision outcome (choice) rather than on the process of the decision making. This pattern is primarily due to the lack of an acceptable unobtrusive tool for investigation of the decision process. Further, the lack of a consistent decision aid in empirical works has hindered the comparison of results. The purpose of this paper is to present a flexible and adaptable computer-based system for empirical examination of information processing. The main thrust of the proposed system is to provide guidelines to the restrictive/channeling approach to system design. This system can be easily modified to suit different experimental research requirements. It should support more realistic decision tasks, which often are criticized in decision experiments. Furthermore, availability of this system should encourage more research work on the process of decision making. The nature of this support system is linked to the literature, and specifications and components of the system are provided.