806 resultados para intelligent decision support systems
Resumo:
Methods of analogous reasoning and case-based reasoning for intelligent decision support systems are considered. Special attention is drawn to methods based on a structural analogy that take the context into account. This work was supported by RFBR (projects 02-07-90042, 05-07-90232).
Resumo:
Development of methods and tools for modeling human reasoning (common sense reasoning) by analogy in intelligent decision support systems is considered. Special attention is drawn to modeling reasoning by structural analogy taking the context into account. The possibility of estimating the obtained analogies taking into account the context is studied. This work was supported by RFBR.
Resumo:
A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism. The chapter emphasizes the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This chapter introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The chapter discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This chapter also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities.
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In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.
Resumo:
In today’s financial markets characterized by constantly changing tax laws and increasingly complex transactions, the demand for family financial planning (FFP) services is rising dramatically. However, the current trend to develop advisory systems that focus mainly on the financial or investment side fails to consider the whole picture of FFP. Separating financial or investment advice from legal and accounting advice may result in conflicting advice or important omissions that could lead to users suffering financial loss. In this paper, we propose a conceptual model for FFP decision-making process, followed by a novel architecture to support an aggregated FFP decision process by utilizing intelligentagents and Web-services technology. A prototype system for supporting FFP decision is presented to demonstrate the advances of the proposed Web-service multi-agentsbased system architecture and business value.
Resumo:
The importance of broadening community participation in environmental decision-making is widely recognized and lack of participation in this process appears to be a perennial problem. In this context, there have been calls from some academics for the more extensive use of geographic information systems (GIS) and distance learning technologies, accessible via the Internet, as a possible means to inform and empower communities. However, a number of problems exist. For instance, at present the scope for online interaction between policy-makers and citizens is currently limited. Contemporary web-based environmental information systems suffer from this lack of interactivity on the one hand and on the other hand from the apparent complexity for the lay user. This paper explores the issue of online community participation at the local level and attempts to construct a framework for a new (and potentially more effective) model of online participatory decision-making. The key components, system architecture and stages of such a model are introduced. This model, referred to as a ‘Community Based Interactive Environmental Decision Support System’, incorporates advanced information technologies, distance learning and community involvement tools which will be applied and evaluated in the field through a pilot project in Tokyo in the summer of 2002.
Resumo:
Many cities around the globe are now considering tourism facilities and their remarkable revenues in order to become competitive in the global economy. In many of these cities a great emphasis is given to the cultural tourism as it plays an important role in the establishment of creative and knowledge-base of cities. The literature points out the importance of local community support in cultural tourism. In such context, the use of new approach and technologies in tourism planning in order to increase the community participation and competitiveness of cities’ cultural assets gains a great significance. This paper advocates a new planning approach for tourism planning, particularly for cultural tourism, to increase the competitiveness of cities. As part of this new approach, the paper introduces the joined up planning approach integrated with a collaborative decision support system: ‘the community-oriented decision support system’. This collaborative planning support system is an effective and efficient tool for cultural tourism planning, which provides a platform for local communities’ participation in the development decision process.
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Introduction Among the many requirements of establishing community health, a healthy urban environment stands out as significant one. A healthy urban environment constantly changes and improves community well-being and expands community resources. The promotion efforts for such an environment, therefore, must include the creation of structures and processes that actively work to dismantle existing community inequalities. In general, these processes are hard to manage; therefore, they require reliable planning and decision support systems. Current and previous practices justify that the use of decision support systems in planning for healthy communities have significant impacts on the communities. These impacts include but are not limited to: increasing collaboration between stakeholders and the general public; improving the accuracy and quality of the decision making process; enhancing healthcare services; and improving data and information availability for health decision makers and service planners. Considering the above stated reasons, this study investigates the challenges and opportunities of planning for healthy communities with the specific aim of examining the effectiveness of participatory planning and decision systems in supporting the planning for such communities. Methods This study introduces a recently developed methodology, which is based on an online participatory decision support system. This new decision support system contributes to solve environmental and community health problems, and to plan for healthy communities. The system also provides a powerful and effective platform for stakeholders and interested members of the community to establish an empowered society and a transparent and participatory decision making environment. Results The paper discusses the preliminary findings from the literature review of this decision support system in a case study of Logan City, Queensland. Conclusion The paper concludes with future research directions and applicability of this decision support system in health service planning elsewhere.
Resumo:
In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.
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This paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (PROgraMme for European Traffic flow with Highest Efficiency and Unprecedented Safety) research programme to achieve an intelligent driver warning system (IDWS). The IDWS includes: visual detection of both generic obstacles and other vehicles, together with their tracking and identification, estimates of time to collision and behavioural modelling of drivers for a variety of scenarios. These application areas are used to show the applicability of neurofuzzy techniques to the wide range of problems required to support an IDWS, and for future fully autonomous vehicles.
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Management of large projects, especially the ones in which a major component of R&D is involved and those requiring knowledge from diverse specialised and sophisticated fields, may be classified as semi-structured problems. In these problems, there is some knowledge about the nature of the work involved, but there are also uncertainties associated with emerging technologies. In order to draw up a plan and schedule of activities of such a large and complex project, the project manager is faced with a host of complex decisions that he has to take, such as, when to start an activity, for how long the activity is likely to continue, etc. An Intelligent Decision Support System (IDSS) which aids the manager in decision making and drawing up a feasible schedule of activities while taking into consideration the constraints of resources and time, will have a considerable impact on the efficient management of the project. This report discusses the design of an IDSS that helps in project planning phase through the scheduling phase. The IDSS uses a new project scheduling tool, the Project Influence Graph (PIG).
Resumo:
Gold Coast Water is responsible for the management of the water and wastewater assets of the City of the Gold Coast on Australia’s east coast. Treated wastewater is released at the Gold Coast Seaway on an outgoing tide in order for the plume to be dispersed before the tide changes and renters the Broadwater estuary. Rapid population growth over the past decade has placed increasing demands on the receiving waters for the release of the City’s effluent. The Seaway SmartRelease Project is designed to optimise the release of the effluent from the City’s main wastewater treatment plant in order to minimise the impact of the estuarine water quality and maximise the cost efficiency of pumping. In order to do this an optimisation study that involves water quality monitoring, numerical modelling and a web based decision support system was conducted. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. These data were then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The decision support system then collects continually measured data such as water levels, interacts with the WWTP SCADA system, runs the models in forecast mode and provides the optimal time window to release the required amount of effluent from the WWTP. The City’s increasing population means that the length of time available for releasing the water with minimal impact may be exceeded within 5 years. Optimising the release of the treated water through monitoring, modelling and a decision support system has been an effective way of demonstrating the limited environmental impact of the expected short term increase in effluent disposal procedures. (PDF contains 5 pages)