948 resultados para Modelling Techniques


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The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

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The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

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This review introduces the methods used to simulate the processes affecting dissolved oxygen (DO) in lowland rivers. The important processes are described and this provides a modelling framework to describe those processes in the context of a mass-balance model. The process equations that are introduced all require (reaction) rate parameters and a variety of common procedures for identifying those parameters are reviewed. This is important because there is a wide range of estimation techniques for many of the parameters. These different techniques elicit different estimates of the parameter value and so there is the potential for a significant uncertainty in the model's inputs and therefore in the output too. Finally, the data requirements for modelling DO in lowland rivers are summarised on the basis of modelling the processes described in this review using a mass-balance model. This is reviewed with regard to what data are available and from where they might be obtained. (C) 2003 Elsevier Science B.V. All rights reserved.

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A Bond Graph is a graphical modelling technique that allows the representation of energy flow between the components of a system. When used to model power electronic systems, it is necessary to incorporate bond graph elements to represent a switch. In this paper, three different methods of modelling switching devices are compared and contrasted: the Modulated Transformer with a binary modulation ratio (MTF), the ideal switch element, and the Switched Power Junction (SPJ) method. These three methods are used to model a dc-dc Boost converter and then run simulations in MATLAB/SIMULINK. To provide a reference to compare results, the converter is also simulated using PSPICE. Both quantitative and qualitative comparisons are made to determine the suitability of each of the three Bond Graph switch models in specific power electronics applications

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For many years in the area of business systems analysis and design, practitioners and researchers alike have been searching for some comprehensive basis on which to evaluate, compare, and engineer techniques that are promoted for use in the modelling of systems' requirements. To date, while many frameworks, factors, and facets have been forthcoming, none appear to be based on a sound theory. In light of this dilemma, over the last 10 years, attention has been devoted by researchers to the use of ontology to provide some theoretical basis for the advancement of the business systems modelling discipline. This paper outlines how we have used a particular ontology for this purpose over the last five years. In particular we have learned that the understandability and the applicability of the selected ontology must be clear for IS professionals, the results of any ontological evaluation must be tempered by economic efficiency considerations of the stakeholders involved, and ontologies may have to be focused for the business purpose and type of user involved in the modelling situation.

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Current initiatives in the field of Business Process Management (BPM) strive for the development of a BPM standard notation by pushing the Business Process Modeling Notation (BPMN). However, such a proposed standard notation needs to be carefully examined. Ontological analysis is an established theoretical approach to evaluating modelling techniques. This paper reports on the outcomes of an ontological analysis of BPMN and explores identified issues by reporting on interviews conducted with BPMN users in Australia. Complementing this analysis we consolidate our findings with previous ontological analyses of process modelling notations to deliver a comprehensive assessment of BPMN.

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The absence of a definitive approach to the design of manufacturing systems signifies the importance of a control mechanism to ensure the timely application of relevant design techniques. To provide effective control, design development needs to be continually assessed in relation to the required system performance, which can only be achieved analytically through computer simulation. The technique providing the only method of accurately replicating the highly complex and dynamic interrelationships inherent within manufacturing facilities and realistically predicting system behaviour. Owing to the unique capabilities of computer simulation, its application should support and encourage a thorough investigation of all alternative designs. Allowing attention to focus specifically on critical design areas and enabling continuous assessment of system evolution. To achieve this system analysis needs to efficient, in terms of data requirements and both speed and accuracy of evaluation. To provide an effective control mechanism a hierarchical or multi-level modelling procedure has therefore been developed, specifying the appropriate degree of evaluation support necessary at each phase of design. An underlying assumption of the proposal being that evaluation is quick, easy and allows models to expand in line with design developments. However, current approaches to computer simulation are totally inappropriate to support the hierarchical evaluation. Implementation of computer simulation through traditional approaches is typically characterized by a requirement for very specialist expertise, a lengthy model development phase, and a correspondingly high expenditure. Resulting in very little and rather inappropriate use of the technique. Simulation, when used, is generally only applied to check or verify a final design proposal. Rarely is the full potential of computer simulation utilized to aid, support or complement the manufacturing system design procedure. To implement the proposed modelling procedure therefore the concept of a generic simulator was adopted, as such systems require no specialist expertise, instead facilitating quick and easy model creation, execution and modification, through simple data inputs. Previously generic simulators have tended to be too restricted, lacking the necessary flexibility to be generally applicable to manufacturing systems. Development of the ATOMS manufacturing simulator, however, has proven that such systems can be relevant to a wide range of applications, besides verifying the benefits of multi-level modelling.

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Practising engineers frequently seek to understand what the effects of various manufacturing strategies will be on the performance of their production facilities. In this situation a computer model can help to provide insight and form predictions about future manufacturing system performance. Various types of modelling methods exist and each provide models that have distinct characteristics. This paper presents a review of popular modelling techniques and, based on the results of a structured experimental study, summarises their capabilities to support the evaluation of manufacturing strategies.

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Predictive models of species distributions are important tools for fisheries management. Unfortunately, these predictive models can be difficult to perform on large waterbodies where fish are difficult to detect and exhaustive sampling is not possible. In recent years the development of Geographic Information Systems (GIS) and new occupancy modelling techniques has improved our ability to predict distributions across landscapes as well as account for imperfect detection. I surveyed the nearshore fish community at 105 sites between Kingston, Ontario and Rockport, Ontario with the objective of modelling geographic and environmental characteristics associated with littoral fish distributions. Occupancy modelling was performed on Round Goby, Yellow perch, and Lepomis spp. Modelling with geographic and environmental covariates revealed the effect of shoreline exposure on nearshore habitat characteristics and the occupancy of Round Goby. Yellow Perch, and Lepomis spp. occupancy was most strongly associated negatively with distance to a wetland. These results are consistent with past research on large lake systems indicate the importance of wetlands and shoreline exposure in determining the fish community of the littoral zone. By examining 3 species with varying rates of occupancy and detection, this study was also able to demonstrate the variable utility of occupancy modelling.

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Dissertação de Mestrado, Estudos Integrados dos Oceanos, 25 de Março de 2013, Universidade dos Açores.