855 resultados para Urban Simulation Model
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Na mesma proporção que fontes de água potável são reduzidas, a competição por elas tem aumentado, conseqüência imediata da expansão de áreas urbanas e de novas demandas agro-industriais. Os conflitos gerados por esta competição tendem a comprometer o desenvolvimento sustentável e o progresso de uma forma geral, uma vez que resultam em perda de eficácia para vultuosos investimentos públicos e privados e em prejuízos para os usuários menos estruturados. Considerando os fatos acima, o objeto deste trabalho é o estabelecimento de cenários de alocação das disponibilidades hídricas entre usuários de água da bacia do Sapucaí-Mirim/Grande, visando determinar a convivência harmoniosa das várias finalidades de uso provenientes do mesmo recurso hídrico. Tal meta poderá ser alcançada através da análise dos indicadores de desempenho - confiabilidade, vulnerabilidade e resiliência - do sistema os quais serão obtidos com o auxílio do modelo de simulação IRAS (Interactive River Aquifer Simulation).
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"HHP-25/11-83(2M)E"--P. [4] of cover.
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Microscopic traffic-simulation tools are increasingly being applied to evaluate the impacts of a wide variety of intelligent transport, systems (ITS) applications and other dynamic problems that are difficult to solve using traditional analytical models. The accuracy of a traffic-simulation system depends highly on the quality of the traffic-flow model at its core, with the two main critical components being the car-following and lane-changing models. This paper presents findings from a comparative evaluation of car-following behavior in a number of traffic simulators [advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN), parallel microscopic simulation (PARAMICS), and Verkehr in Statiten-simulation (VISSIM)]. The car-following algorithms used in these simulators have been developed from a variety of theoretical backgrounds and are reported to have been calibrated on a number of different data sets. Very few independent studies have attempted to evaluate the performance of the underlying algorithms based on the same data set. The results reported in this study are based on a car-following experiment that used instrumented vehicles to record the speed and relative distance between follower and leader vehicles on a one-lane road. The experiment was replicated in each tool and the simulated car-following behavior was compared to the field data using a number of error tests. The results showed lower error values for the Gipps-based models implemented in AIMSUN and similar error values for the psychophysical spacing models used in VISSIM and PARAMICS. A qualitative drift and goal-seeking behavior test, which essentially shows how the distance headway between leader and follower vehicles should oscillate around a stable distance, also confirmed the findings.
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Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant
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Expert systems, and artificial intelligence more generally, can provide a useful means for representing decision-making processes. By linking expert systems software to simulation software an effective means of including these decision-making processes in a simulation model can be achieved. This paper demonstrates how a commercial-off-the-shelf simulation package (Witness) can be linked to an expert systems package (XpertRule) through a Visual Basic interface. The methodology adopted could be used for models, and possibly software, other than those presented here.
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A discrete event simulation model was developed and used to estimate the storage area required for a proposed overseas textile manufacturing facility. It was found that the simulation was able to achieve this because of its ability to both store attribute values and to show queuing levels at an individual product level. It was also found that the process of undertaking the simulation project initiated useful discussions regarding the operation of the facility. Discrete event simulation is shown to be much more than an exercise in quantitative analysis of results and an important task of the simulation project manager is to initiate a debate among decision makers regarding the assumptions of how the system operates.
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The potential for the use of DEA and simulation in a mutually supporting role in guiding operating units to improved performance is presented. An analysis following a three-stage process is suggested. Stage one involves obtaining the data for the DEA analysis. This can be sourced from historical data, simulated data or a combination of the two. Stage two involves the DEA analysis that identifies benchmark operating units. In the third stage simulation can now be used in order to offer practical guidance to operating units towards improved performance. This can be achieved by the use of sensitivity analysis of the benchmark unit using a simulation model to offer direct support as to the feasibility and efficiency of any variations in operating practices to be tested. Alternatively, the simulation can be used as a mechanism to transmit the practices of the benchmark unit to weaker performing units by building a simulation model of the weaker unit to the process design of the benchmark unit. The model can then compare performance of the current and benchmark process designs. Quantifying improvement in this way provides a useful driver to any process change initiative that is required to bring the performance of weaker units up to the best in class. © 2005 Operational Research Society Ltd. All rights reserved.
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Simulation modelling has been used for many years in the manufacturing sector but has now become a mainstream tool in business situations. This is partly because of the popularity of business process re-engineering (BPR) and other process based improvement methods that use simulation to help analyse changes in process design. This textbook includes case studies in both manufacturing and service situations to demonstrate the usefulness of the approach. A further reason for the increasing popularity of the technique is the development of business orientated and user-friendly Windows-based software. This text provides a guide to the use of ARENA, SIMUL8 and WITNESS simulation software systems that are widely used in industry and available to students. Overall this text provides a practical guide to building and implementing the results from a simulation model. All the steps in a typical simulation study are covered including data collection, input data modelling and experimentation.
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This paper describes the use of simulation in a large manufacturing organisation and analyses how it could have been used more fully. Although the benefits from using simulation were clear, it was seen that the technique could have been deployed more effectively by considering the organisational context of the use. From the analysis of the case study, certain recommendations are made on how to maximise the benefits from simulation within the organisation, thereby extending the benefits from what is often a considerable investment in developing a simulation model. Recent developments in simulation software in terms of improvements in usability and integration with organisational data are seen to increase the feasibility of a wider role for simulation if the organisational barriers discussed can be overcome.
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A case study demonstrates the use of a process-based approach to change regarding the implementation of an information system for road traffic accident reporting in a UK police force. The supporting tools of process mapping and business process simulation are used in the change process and assist in communicating the current process design and people's roles in the overall performance of that design. The simulation model is also used to predict the performance of new designs incorporating the use of information technology. The approach is seen to have a number of advantages in the context of a public sector organisation. These include the ability for personnel to move from a traditional grouping of staff in occupational groups with relationships defined by reporting requirements to a view of their role in a process, which delivers a performance to a customer. By running the simulation through time it is also possible to gauge how changes at an operational level can lead to the meeting of strategic targets over time. Also the ability of simulation to proof new designs was seen as particularly important in a government agency were past failures of information technology investments had contributed to a more risk averse approach to their implementation. © 2004 Elsevier Ltd. All rights reserved.
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An investigation is carried out into the design of a small local computer network for eventual implementation on the University of Aston campus. Microprocessors are investigated as a possible choice for use as a node controller for reasons of cost and reliability. Since the network will be local, high speed lines of megabit order are proposed. After an introduction to several well known networks, various aspects of networks are discussed including packet switching, functions of a node and host-node protocol. Chapter three develops the network philosophy with an introduction to microprocessors. Various organisations of microprocessors into multicomputer and multiprocessor systems are discussed, together with methods of achieving reliabls computing. Chapter four presents the simulation model and its implentation as a computer program. The major modelling effort is to study the behaviour of messages queueing for access to the network and the message delay experienced on the network. Use is made of spectral analysis to determine the sampling frequency while Sxponentially Weighted Noving Averages are used for data smoothing.
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Investment in transport infrastructure can be highly sensitive to uncertainty. The scale and lead time of strategic transport programmes are such that they require continuing policy support and accurate forecasting. Delay, cost escalation and abandonment of projects often result if these conditions are not present. In Part One the physical characteristics of infrastructure are identified as a major constraint on planning processes. The extent to which strategies and techniques acknowledge these constraints is examined. A simple simulation model is developed to evaluate the effects on system development of variations in the scale and lead time of investments. In Part Two, two case studies of strategic infrastructure investment are analysed. The absence of a policy consensus for airport location was an important factor in the delayed resolution of the Third London Airport issue. In London itself, the traffic and environmental effects of major highway investment ultimately resulted in the abandonment of plans to construct urban motorways. In both cases, the infrastructure implications of alternative strategies are reviewed with reference to the problems of uncertainty. In conclusion, the scale of infrastructure investment is considered the most important of the constraints on the processes of transport planning. Adequate appraisal of such constraints may best be achieved by evaluation more closely aligned to policy objectives.
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The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself.
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Calibration of stochastic traffic microsimulation models is a challenging task. This paper proposes a fast iterative probabilistic precalibration framework and demonstrates how it can be successfully applied to a real-world traffic simulation model of a section of the M40 motorway and its surrounding area in the U.K. The efficiency of the method stems from the use of emulators of the stochastic microsimulator, which provides fast surrogates of the traffic model. The use of emulators minimizes the number of microsimulator runs required, and the emulators' probabilistic construction allows for the consideration of the extra uncertainty introduced by the approximation. It is shown that automatic precalibration of this real-world microsimulator, using turn-count observational data, is possible, considering all parameters at once, and that this precalibrated microsimulator improves on the fit to observations compared with the traditional expertly tuned microsimulation. © 2000-2011 IEEE.
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Timely warning of the public during large scale emergencies is essential to ensure safety and save lives. This ongoing study proposes an agent-based simulation model to simulate the warning message dissemination among the public considering both official channels and unofficial channels The proposed model was developed in NetLogo software for a hypothetical area, and requires input parameters such as effectiveness of each official source (%), estimated time to begin informing others, estimated time to inform others and estimated percentage of people (who do not relay the message). This paper demonstrates a means of factoring the behaviour of the public as informants into estimating the effectiveness of warningdissemination during large scale emergencies. The model provides a tool for the practitioner to test the potential impact of the informal channels on the overall warning time and sensitivity of the modelling parameters. The tool would help the practitioners to persuade evacuees to disseminate the warning message informing others similar to the ’Run to thy neighbour campaign conducted by the Red cross.