850 resultados para Biomass dynamic models


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Este trabalho investiga como os padrões de compras de consumidores de bens estocáveis são afetados por suas expectativas de preços. Usando um modelo dinâmico padrão de maximização da utilidade, deriva-se uma expressão analítica para as compras dos consumidores como uma função das suas expectativas em relação aos preços futuros. Em seguida, uma versão mais tratável do modelo é construída, de forma a ilustrar graficamente como os diferentes tipos de expectativas de preços implicam diferentes padrões de compras dos consumidores. Além disso, na aplicação empírica, investigo qual o modelo de expectativas de preços, entre aqueles comumente utilizados na literatura, é consistente com os dados. Por fim, encontra-se suficiente heterogeneidade em expectativa de preços dos consumidores. Mostra-se que famílias de pequeno porte acreditam que os preços seguem um processo de Markov de primeira ordem, enquanto famílias de alta renda são racionais.

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In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.

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In recent years, many researchers in the field of biomedical sciences have made successful use of mathematical models to study, in a quantitative way, a multitude of phenomena such as those found in disease dynamics, control of physiological systems, optimization of drug therapy, economics of the preventive medicine and many other applications. The availability of good dynamic models have been providing means for simulation and design of novel control strategies in the context of biological events. This work concerns a particular model related to HIV infection dynamics which is used to allow a comparative evaluation of schemes for treatment of AIDS patients. The mathematical model adopted in this work was proposed by Nowak & Bangham, 1996 and describes the dynamics of viral concentration in terms of interaction with CD4 cells and the cytotoxic T lymphocytes, which are responsible for the defense of the organism. Two conceptually distinct techniques for drug therapy are analyzed: Open Loop Treatment, where a priori fixed dosage is prescribed and Closed Loop Treatment, where the doses are adjusted according to results obtained by laboratory analysis. Simulation results show that the Closed Loop Scheme can achieve improved quality of the treatment in terms of reduction in the viral load and quantity of administered drugs, but with the inconvenience related to the necessity of frequent and periodic laboratory analysis.

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This work analyses a real time orbit estimator using the raw navigation solution provided by GPS receivers. The estimation algorithm considers a Kalman filter with a rather simple orbit dynamic model and random walk modeling of the receiver clock bias and drift. Using the Topex/Poseidon satellite as test bed, characteristics of model truncation, sampling rates and degradation of the GPS receiver (Selective Availability) were analysed. Copyright © 2007 by ABCM.

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The cost of maintenance makes up a large part of total energy costs in ruminants. Metabolizable energy (ME) requirement for maintenance (MEm) is the daily ME intake that exactly balances heat energy (HE). The net energy requirement for maintenance (NEm) is estimated subtracting MEm from the HE produced by the processing of the diet. Men cannot be directly measured experimentally and is estimated by measuring basal metabolism in fasted animals or by regression measuring the recovered energy in fed animals. MEm and NEm usually, but not always, are expressed in terms of BW0.75. However, this scaling factor is substantially empirical and its exponent is often inadequate, especially for growing animals. MEm estimated by different feeding systems (AFRC, CNCPS, CSIRO, INRA, NRC) were compared by using dairy cattle data. The comparison showed that these systems differ in the approaches used to estimate MEm and for its quantification. The CSIRO system estimated the highest MEm, mostly because it includes a correction factor to increase ME as the feeding level increases. Relative to CSIRO estimates, those of NRC, INRA, CNCPS, and AFRC were on average 0.92, 0.86, 0.84, and 0.78, respectively. MEm is affected by the previous nutritional history of the animals. This phenomenon is best predicted by dynamic models, of which several have been published in the last decades. They are based either on energy flows or on nutrient flows. Some of the different approaches used were described and discussed.

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In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.

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Muitas são os fatores, apontadas pela literatura pertinente, acerca das causas do desmatamento da Amazônia Legal brasileira. Desde aspectos endógenos como as condições edafo-climáticas, a aspectos relacionados à ação antrópica como os movimentos populacionais, o crescimento urbano e, em especial, as ações autônomas ou induzidas dos diversos agentes econômicos públicos e privados que têm atuado na região, configurando historicamente os processos de ocupação do solo e aproveitamento econômico do espaço amazônico. Este artigo tem como objetivo realizar um teste de causalidade, no sentido de Granger, nas principais variáveis sugeridas como importantes para explicar o desmatamento da Amazônia Legal, no período de 1997 a 2006. A metodologia a ser empregada se baseia em modelos dinâmicos para dados em painel, desenvolvidos por Holtz-Eakin et al. (1988) e Arellano-Bond (1991), que desenvolveram um teste de causalidade baseado no artigo seminal de Granger (1969). Entre os principais resultados obtidos está a constatação empírica de que existe uma causalidade bidirecional entre desmatamento e as áreas de culturas permanente e temporária, bem como o tamanho do rebanho bovino.

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Nesta dissertação apresenta-se o problema de redução de ordem de modelos dinâmicos lineares, sob o ponto de vista de otimização via Algoritmos Genéticos. Uma função custo, obtida a partir da norma dos coeficientes do numerador da função de transferência do erro entre o modelo original e o reduzido, e minimizada por meio de um algoritmo genético, com consequente calculo dos parâmetros do modelo reduzido. O procedimento e aplicado em alguns exemplos que demonstram a validade da abordagem.

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Esta dissertação apresenta uma metodologia baseada em algoritmo genético (AG) para determinar modelos dinâmicos equivalentes de parques eólicos com geradores de indução em gaiola de esquilo ( GIGE) e geradores de indução duplamente alimentados ( GIDA), apresentando parâmetros elétricos e mecânicos distintos. A técnica se baseia em uma formulação multiobjetiva solucionada por um AG para minimizar os erros quadráticos das potências ativa e reativa entre modelo de um único gerador equivalente e o modelo do parque eólico investigado. A influência do modelo equivalente do parque eólico no comportamento dinâmico dos geradores síncronos é também investigada por meio do método proposto. A abordagem é testada em um parque eólico de 10MW composto por quatro turbinas eólicas ( 2x2MW e 2x3MW), consistindo alternadamente de geradores GIGE e GIDA interligados a uma barra infinita e posteriormente a rede elétrica do IEEE 14 barras. Os resultados obtidos pelo uso do modelo dinâmico detalhado para a representação do parque eólico são comparados aos do modelo equivalente proposto para avaliar a precisão e o custo computacional do modelo proposto.

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The friction phenomena is present in mechanical systems with two surfaces that are in contact, which can cause serious damage to structures. Your understanding in many dynamic problems became the target of research due to its nonlinear behavior. It is necessary to know and thoroughly study each existing friction model found in the literature and nonlinear methods to define what will be the most appropriate to the problem in question. One of the most famous friction model is the Coulomb Friction, which is considered in the studied problems in the French research center Laboratoire de Mécanique des Structures et des Systèmes Couplés (LMSSC), where this search began. Regarding the resolution methods, the Harmonic Balance Method is generally used. To expand the knowledge about the friction models and the nonlinear methods, a study was carried out to identify and study potential methodologies that can be applied in the existing research lines in LMSSC and then obtain better final results. The identified friction models are divided into static and dynamic. Static models can be Classical Models, Karnopp Model and Armstrong Model. The dynamic models are Dahl Model, Bliman and Sorine Model and LuGre Model. Concerning about nonlinear methods, we study the Temporal Methods and Approximate Methods. The friction models analyzed with the help of Matlab software are verified from studies in the literature demonstrating the effectiveness of the developed programming

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Pós-graduação em Docência para a Educação Básica - FC

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the driver's commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e. g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H-infinity controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

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The aim of this Thesis is to obtain a better understanding of the mechanical behavior of the active Alto Tiberina normal fault (ATF). Integrating geological, geodetic and seismological data, we perform 2D and 3D quasi-static and dynamic mechanical models to simulate the interseismic phase and rupture dynamic of the ATF. Effects of ATF locking depth, synthetic and antithetic fault activity, lithology and realistic fault geometries are taken in account. The 2D and 3D quasi-static model results suggest that the deformation pattern inferred by GPS data is consistent with a very compliant ATF zone (from 5 to 15 km) and Gubbio fault activity. The presence of the ATF compliant zone is a first order condition to redistribute the stress in the Umbria-Marche region; the stress bipartition between hanging wall (high values) and footwall (low values) inferred by the ATF zone activity could explain the microseismicity rates that are higher in the hanging wall respect to the footwall. The interseismic stress build-up is mainly located along the Gubbio fault zone and near ATF patches with higher dip (30°dynamic models demonstrate that the magnitude expected, after that an event is simulated on the ATF, can decrease if we consider the fault plane roughness.