Seleção da largura dos dentes ântero-superiores de próteses totais: estudo de quatro métodos fundamentados na posição dos caninos em três grupos raciais da população brasileira

Pós-graduação em Reabilitação Oral - FOAR

Previsão de carga multinodal usando a rede neural ART-ARTMAP fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Mapas pluviométricos médios mensais no verão para o estado do Paraná, utilizando métodos geoestatísticos

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Metodologias de inteligência computacional aplicadas ao problema de previsão de carga a curto prazo

Diversas atividades de planejamento e operação em sistemas de energia elétrica dependem do conhecimento antecipado e preciso da demanda de carga elétrica. Por este motivo, concessionárias de geração e distribuição de energia elétrica cada vez mais fazem uso de tecnologias de previsão de carga. Essas previsões podem ter um horizonte de curtíssimo, curto, médio ou longo prazo. Inúmeros métodos estatísticos vêm sendo utilizados para o problema de previsão. Todos estes métodos trabalham bem em condições normais, entretanto deixam a desejar em situações onde ocorrem mudanças inesperadas nos parâmetros do ambiente. Atualmente, técnicas baseadas em Inteligência Computacional vêm sendo apresentadas na literatura com resultados satisfatórios para o problema de previsão de carga. Considerando então a importância da previsão da carga elétrica para os sistemas de energia elétrica, neste trabalho, uma nova abordagem para o problema de previsão de carga via redes neurais Auto-Associativas e algoritmos genéticos é avaliada. Três modelos de previsão baseados em Inteligência Computacional são também apresentados tendo seus desempenhos avaliados e comparados com o sistema proposto. Com os resultados alcançados, pôde-se verificar que o modelo proposto se mostrou satisfatório para o problema de previsão, reforçando assim a aplicabilidade de metodologias de inteligência computacional para o problema de previsão de cargas.

Determinação de vazões extremas para diversos períodos de retorno para o Rio Paraguai utilizando métodos estatísticos

No presente trabalho foram analisadas as distribuições de probabilidade teórica Normal, Log-Normal, Exponencial, Gama e Weibull, para estimar as vazões máximas e mínimas anuais para o rio Paraguai, utilizando dados de uma estação fluviométrica localizado na cidade de Cáceres-MT. Os testes de Kolmogorov-Smirnov e Qui-Quadrado foram utilizados para verificar a aderência das probabilidades estimadas às freqüências observadas. A série utilizada compreende vazões máximas e mínimas anuais dos anos de 1966 a 2003, excluindo- se dados com falhas. Verificou-se que o melhor ajuste dos valores anuais de vazão máximas e mínimas são referentes a distribuição Gama e Weibull, respectivamente, conforme demonstrado pelo teste de Kolmogorov-Smirnov. Palavras-chave: Previsão de Vazão, teste de aderência.

Interferência do método de previsão populacional no desempenho hidráulico de uma rede coletora de esgoto sanitário

The non existence of sewage services creates an unhealthy environmental, causing impact extremely prejudicial to the human health. In Brazil, this item represents the biggest deficit in the basic sanitation these days, and only about 50% of the population is attended. The sewage collection network is a needful system for the basic sanitation. Between the parameters of the project of a system of collection and sewage transportation, the definition of the population that will be attended is one of the most important variables, and that should be done based on criterion of population growth and in accordant to directrix presents in the comprehensive city plan. In this paper, were evaluated methods of growth based on the geometric growth rate, on the population density and on the number of residents per dwelling, and also mathematics models of growth prediction, emphasizing in the geometric growth and on the logistic curve method. That way, the goal of this paper were value the hydraulic performance in one of the watersheds delimited by the sewage network magnification work existent in the city of Cacoal–RO. Using simulation with different scenarios, the results pointed that the hydraulic performance of the system were strongly affected by the population determination method used. For the same drained area the diameters range from 150 to 250 mm as well as the trench’s deep, where some stretches exceeded the maximum values contained in the standard. Besides, the variation of the sewage contribution rate due the population variation estimated in different scenarios, led to alterations in others important project parameters, such as slope, shallow pool, tensile stress and spreading velocity

Métodos econométricos para a análise do índice de inflação no Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Desenvolvimento, validação, avaliação da incerteza de medição e análise de custos de método baseado em espectroscopia no infravermelho e análise multivariada para previsão de parâmetros de qualidade de amostras de E85

Pós-graduação em Química - IQ

Modelagem auto-regressiva na previsão de demanda dos produtos de uma empresa do setor químico

Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

Previsão da capacidade de carga de estacas escavadas em solo arenoso da região de Araquari-SC

In Geotechnical engineering the foundation projects depend on the bearing capacity and the acceptable displacements. One of the possible ways to predict the bearing capacity of foundations is through semi-empirical statistical methods which correlate in-situ tests (SPT and CPT). The piles breaking loads are defined by the interpretation of the load x head displacement curve and the experimental data acquired through the load test. In this work it is studied the behavior of bored piles executed in the Araquari/SC region, comparing the bearing capacity values predicted by the methods DECOURT & QUARESMA MODIFICADO (1996), AOKI & VELLOSO MODIFICADO MONTEIRO (2000), MILITITISKY E ALVES (1985), DECOURT & QUARESMA (1978), MÉTODO DE AOKI & VELLOSO (1975) e PHILOPANNAT (1986), with the results of the load test, evaluating their differences and discussing parameters that have direct effects on the prediction

Modelagem auto-regressiva na previsão de demanda dos produtos de uma empresa do setor químico

Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

Previsão da capacidade de carga de estacas escavadas em solo arenoso da região de Araquari-SC

In Geotechnical engineering the foundation projects depend on the bearing capacity and the acceptable displacements. One of the possible ways to predict the bearing capacity of foundations is through semi-empirical statistical methods which correlate in-situ tests (SPT and CPT). The piles breaking loads are defined by the interpretation of the load x head displacement curve and the experimental data acquired through the load test. In this work it is studied the behavior of bored piles executed in the Araquari/SC region, comparing the bearing capacity values predicted by the methods DECOURT & QUARESMA MODIFICADO (1996), AOKI & VELLOSO MODIFICADO MONTEIRO (2000), MILITITISKY E ALVES (1985), DECOURT & QUARESMA (1978), MÉTODO DE AOKI & VELLOSO (1975) e PHILOPANNAT (1986), with the results of the load test, evaluating their differences and discussing parameters that have direct effects on the prediction

Estudo da previsão da carga de ruptura de estacas pré-moldadas de concreto

The piles are one of the most important types of solution adopted for the foundation of buildings. They are responsible for transmitting to the soil in deepe r and resistant layers loads from structures. The interaction of the foundation element with the soil is a very important variable, making indispensable your domain in order to determine the strength of the assembly and establish design criteria for each c ase of application of the pile. In this research analyzes were performed f rom experiments load tests for precast concrete piles and inve stigations of soil of type SPT, a study was performed for obtaining the ultimate load capacity of the foundation through methods extrapolation of load - settlement curve , semi - empirical and theoretic . After that, were realized comparisons between the different methods used for two types of soil a granular behavior and other cohesive. For obtaining soil paramet ers to be used i n the methods were established empirical correlations with the standard penetration number (NSPT). The charge - settlement curves of the piles are also analyzed. In the face of established comparisons was indicated the most reliable semiempirical method Déco urt - Quaresma as the most reliable for estimating the tensile strength for granular and cohesive soils. Meanwhile, among the methods studied extrapolation is recommended method of Van der Veen as the most appropriate for predicting the tensile strength.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.