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Experiments on theories: the construction of scientific computer simulationDowling, Deborah Caitlin Unknown Date (has links) (PDF)
Scientific computer simulation involves interacting with a mathematical model, in a way that is analogous to performing a laboratory experiment. Based on interviews with scientists, using a framework of grounded theory and symbolic interactionist sociology, the thesis describes crucial features of this novel mode of scientific work. A dualistic comparison of simulation with ‘theory’ and ‘experiment’ (in the second chapter) gives rise to two apparently independent discussions: of the ‘experilnental’ practices associated with simulation (chapter three), and of the ‘theoretical’ concerns that shape the technique (chapter four). Those discussions are drawn together in chapter five, which describes the interdependence of those two essential aspects of simulation. (For complete abstract open document)
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Optimised dose titration for Duodopatreatment based on simulation experiments– implementation in a decision supportsystemCHen, Canghai January 2009 (has links)
The aim of this work was to design a set of rules for levodopa infusion dose adjustment in Parkinson’s disease based on a simulation experiments. Using this simulator, optimal infusions dose in different conditions were calculated. There are seven conditions (-3 to +3)appearing in a rating scale for Parkinson’s disease patients. By finding mean of the differences between conditions and optimal dose, two sets of rules were designed. The set of rules was optimized by several testing. Usefulness for optimizing the titration procedure of new infusion patients based on rule-based reasoning was investigated. Results show that both of the number of the steps and the errors for finding optimal dose was shorten by new rules. At last, the dose predicted with new rules well on each single occasion of majority of patients in simulation experiments.
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De l'utilisation de méta-modèles pour la modélisation et l'analyse de la réponse radar des forêts / On the use of metamodeling for modeling and analysis of the radar response of forestsPiteros, Panagiotis 15 April 2016 (has links)
Dans ce travail, une nouvelle approche de conduite des observations radar de la forêt est proposée. Elle combine des méthodes statistiques pour l’analyse de sensibilité et les plans d’expériences numériques séquentiels et un code de calcul simulant la rétrodiffusion d’une forêt en vue de l’élaboration d’un modèle approché (métamodèle) à moindre coût numérique. L’introduction de ces outils mathématiques a pour objectif d’aider à la planification et à l’exécution des simulations radar et à l’organisation et l’analyse de leurs résultats. D’une part, les techniques de l’analyse de sensibilité sont appliquées afin de classer par ordre d’importance les paramètres d’entrée du modèle et d’identifier les paramètres de la forêt les plus significatifs ainsi que leurs effets sur le signal radar. D’autre part, la construction d’un métamodèle adaptable accélère le code de calcul, en préservant la physique du phénomène. Le cadre opérationnel de ce modèle approché sert finalement à introduire le principe du radar cognitif dans notre stratégie. Dans ce cas, une analyse rapide du signal reçu est nécessaire pour concevoir, en temps réel, le nouveau signal à émettre. De cette façon, les observations du radar simulées incluent en temps réel l’effet de l’environnement illuminé grâce aux simulations plus rapides et ciblées. / In this work, a new approach to conduct the radar observations of forests is proposed. It combines statistical methods for sensitivity analysis and adaptive design of simulation experiments and a numerical code simulating the the forest backscattering for the use of a approximate model (metamodel) with less computational cost. The introduction of these mathematical tools has as an objective to assist the design and the execution of radar simulations and at the organization and the analysis of their results. On the one hand, the sensitivity analysis techniques were applied in order to classify the input parameters by means of their importance and to identify the most significant forest parameters as well as their effects on the radar signal. On the other hand, the construction of an adaptive metamodel accelerates the simulation model, while keeping the physics of the phenomenom. The operational frame of this approximate model serves finally in the introduction of the cognitive radar principle in our strategy. In that case, a fast analysis of the received signal is necessary to design, in real time, the new signal to be emitted. That way, the simulated radar observations take into account in real time the effect of the illuminated environment, thanks to the more focused and fast simulations.
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