591 resultados para Inferência bayesiana


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[ES] En este trabajo se presenta una alternativa al proceso de tarificación en los seguros generales (no vida), que pretende garantizar mayor estabilidad para la compañía aseguradora. Para ello incorporaremos entradas más flexibles que las utilizadas en un proceso bayesiano clásico.

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[ES] Este trabajo presenta algunas posibilidades de aprovechamiento de la opinión cualitativa de un auditor. Se desarrolla en torno a un caso ficticio que contiene las ideas básicas sobre la metodología expuesta.

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En esta tesis se desarrolla un modelo físico-matemático, original, que permite simular el comportamiento de las máquinas de visión, en particular las máquinas ópticas digitales, cuando reciben información a través de la luz reflejada por los mensurandos. El modelo desarrollado se lia aplicado para la determinación de los parámetros que intervienen en el proceso de caracterización de formas geométricas básicas, tales como líneas, círculos y elipses. También se analizan las fuentes de error que intervienen a lo largo de la cadena metrológica y se proponen modelos de estimación de las incertidumbres de medida a través un nuevo enfoque basado en estadística bayesiana y resolución subpíxel. La validez del modelo se ha comprobado por comparación de los resultados teóricos, obtenidos a partir de modelos virtuales y simulaciones informáticas, y los reales, obtenidos mediante la realización de medidas de diferentes mensurandos del ámbito electromecánico y de dimensiones submilimétricas. Utilizando el modelo propuesto, es posible caracterizar adecuadamente mensurandos a partir del filtrado, segmentación y tratamiento matemático de las imágenes. El estudio experimental y validación definitiva de los resultados se ha realizado en el Laboratorio de Metrología Dimensional de la Escuela Técnica Superior de Ingeniería y Diseño Industrial de la Universidad Politécnica de Madrid. Los modelos desarrollados se han implementado sobre imágenes obtenidas con la máquina de visión marca TESA, modelo VISIO 300. Abstract In this PhD Thesis an original mathematic-physic model has been developed. It allows simulating the behaviour of the vision measuring machines, in particular the optical digital machines, where they receive information through the light reflected by the measurands. The developed model has been applied to determine the parameters involved in the process of characterization of basic geometrical features such as lines, circles and ellipses. The error sources involved along the metrological chain also are analyzed and new models for estimating measurement uncertainties through a new approach based on Bayesian statistics and subpixel resolution are proposed. The validity of the model has been verified by comparing the theoretical results obtained from virtual models and computer simulations, with actual ones, obtained by measuring of various measurands belonging to the electromechanical field and of submillimeter dimensions. Using the proposed model, it is possible to properly characterize measurands from filtering, segmentation and mathematical processing of images. The experimental study and final validation of the results has been carried out in the "Laboratorio de Metrología Dimensional" (Dimensional Metrology Laboratory) at the Escuela Técnica Superior de Ingeniería y Diseño Industrial (ETSIDI) (School of Engineering and Industrial Design) at Universidad Politécnica de Madrid (UPM). The developed models have been implemented on images obtained with the vision measuring machine of the brand TESA, model VISIO 300.

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Comunicación presentada en el I Congrés Català d’Intel·ligència Artificial, Tarragona, Octubre de 1998.

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Este trabalho tem com objetivo abordar o problema de alocação de ativos (análise de portfólio) sob uma ótica Bayesiana. Para isto foi necessário revisar toda a análise teórica do modelo clássico de média-variância e na sequencia identificar suas deficiências que comprometem sua eficácia em casos reais. Curiosamente, sua maior deficiência não esta relacionado com o próprio modelo e sim pelos seus dados de entrada em especial ao retorno esperado calculado com dados históricos. Para superar esta deficiência a abordagem Bayesiana (modelo de Black-Litterman) trata o retorno esperado como uma variável aleatória e na sequência constrói uma distribuição a priori (baseado no modelo de CAPM) e uma distribuição de verossimilhança (baseado na visão de mercado sob a ótica do investidor) para finalmente aplicar o teorema de Bayes tendo como resultado a distribuição a posteriori. O novo valor esperado do retorno, que emerge da distribuição a posteriori, é que substituirá a estimativa anterior do retorno esperado calculado com dados históricos. Os resultados obtidos mostraram que o modelo Bayesiano apresenta resultados conservadores e intuitivos em relação ao modelo clássico de média-variância.

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This study aimed to determine if accounting and governance indicators are relevant to foresee the stages of financial stress of companies by using a logistic regression. With the formation of two samples was possible to verify if the inclusion of insolvency data defined by cash flow shortage events were relevant to increase model capacity for prediction of insolvency. The remaining insolvency stages were judicial reorganization and bankruptcy. The control sample is formed by healthy companies, from the same sector and size. The period of analysis includes events that occurred between January 2008 and March 2016. The main variables that showed significant results to predict insolvency states, a year before the event happens, were Profitability, Efficiency and Payment Capacity indicators. The Governance indicator was only significant to predict insolvency arising from judicial reorganization and bankruptcy. Among the models studied, the most accurate model presented total correctness capacity of 88,7%, classifying correctly 88% of solvent companies and 89,3% of insolvent companies. The results indicate the usefulness of financial indicators of Payment Capacity, Efficiency and Profitability, as well as the Governance variable, to discriminate the insolvency of companies.

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The plant metabolism consists of a complex network of physical and chemical events resulting in photosynthesis, respiration, synthesis and degradation of organic compounds. This is only possible due to the different kinds of responses to many environmental variations that a plant could be subject through evolution, leading also to conquering new surroundings. The glyoxylate cycle is a metabolic pathway found in glyoxysomes plant, which has unique role in the seedling establishment. Considered as a variation of the citric acid cycle, it uses an acetyl coenzyme A molecule, derived from lipids beta-oxidation to synthesize compounds which are used in carbohydrate synthesis. The Malate synthase (MLS) and Isocitrate lyase (ICL) enzyme of this cycle are unique and essential in regulating the biosynthesis of carbohydrates. Because of the absence of decarboxylation steps as rate-limiting steps, detailed studies of molecular phylogeny and evolution of these proteins enables the elucidation of the effects of this route presence in the evolutionary processes involved in their distribution across the genome from different plant species. Therefore, the aim of this study was to establish a relationship between the molecular evolution of the characteristics of enzymes from the glyoxylate cycle (isocitrate lyase and malate synthase) and their molecular phylogeny, among green plants (Viridiplantae). For this, amino acid and nucleotide sequences were used, from online repositories as UniProt and Genbank. Sequences were aligned and then subjected to an analysis of the best-fit substitution models. The phylogeny was rebuilt by distance methods (neighbor-joining) and discrete methods (maximum likelihood, maximum parsimony and Bayesian analysis). The identification of structural patterns in the evolution of the enzymes was made through homology modeling and structure prediction from protein sequences. Based on comparative analyzes of in silico models and from the results of phylogenetic inferences, both enzymes show significant structure conservation and their topologies in agreement with two processes of selection and specialization of the genes. Thus, confirming the relevance of new studies to elucidate the plant metabolism from an evolutionary perspective

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Wireless sensor networks (WSN) have gained ground in the industrial environment, due to the possibility of connecting points of information that were inaccessible to wired networks. However, there are several challenges in the implementation and acceptance of this technology in the industrial environment, one of them the guaranteed availability of information, which can be influenced by various parameters, such as path stability and power consumption of the field device. As such, in this work was developed a tool to evaluate and infer parameters of wireless industrial networks based on the WirelessHART and ISA 100.11a protocols. The tool allows quantitative evaluation, qualitative evaluation and evaluation by inference during a given time of the operating network. The quantitative and qualitative evaluation are based on own definitions of parameters, such as the parameter of stability, or based on descriptive statistics, such as mean, standard deviation and box plots. In the evaluation by inference uses the intelligent technique artificial neural networks to infer some network parameters such as battery life. Finally, it displays the results of use the tool in different scenarios networks, as topologies star and mesh, in order to attest to the importance of tool in evaluation of the behavior of these networks, but also support possible changes or maintenance of the system.

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This work aims to obtain a low-cost virtual sensor to estimate the quality of LPG. For the acquisition of data from a distillation tower, software HYSYS ® was used to simulate chemical processes. These data will be used for training and validation of an Artificial Neural Network (ANN). This network will aim to estimate from available simulated variables such as temperature, pressure and discharge flow of a distillation tower, the mole fraction of pentane present in LPG. Thus, allowing a better control of product quality

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Este trabalho apresenta um estudo da influência de diferentes materiais de cobertura no conforto térmico de instalações destinadas à criação de frangos de corte. A pesquisa foi desenvolvida no Câmpus Experimental da UNESP de Dracena - SP. Quatro protótipos em escala real foram construídos, com área de 28 m² cada, cobertos com telha reciclada à base de embalagens longa vida, telha cerâmica, telha cerâmica pintada de branco e telha de fibrocimento. Os dados foram coletados durante o período de inverno de 2007, totalizando 90 dias. Com esses dados, foram calculados os índices de conforto térmico Carga Térmica Radiante (CTR) e a variável ambiental (Ta). Uma análise estatística por inferência e descritiva foi realizada com os valores do índice de conforto térmico e da variável ambiental. Com os resultados obtidos, é possível afirmar que a telha reciclada apresentou índices de conforto térmico semelhantes àqueles encontrados para as telhas cerâmicas. O protótipo coberto com telha de fibrocimento apresentou os maiores índices, e o coberto com telha cerâmica branca, os menores índices de conforto térmico. No entanto para o período de inverno e para os horários avaliados, todas as instalações apresentaram índices de conforto térmico fora da zona de termoneutralidade do frango de corte.

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Neste artigo apresentamos uma análise Bayesiana para o modelo de volatilidade estocástica (SV) e uma forma generalizada deste, cujo objetivo é estimar a volatilidade de séries temporais financeiras. Considerando alguns casos especiais dos modelos SV usamos algoritmos de Monte Carlo em Cadeias de Markov e o software WinBugs para obter sumários a posteriori para as diferentes formas de modelos SV. Introduzimos algumas técnicas Bayesianas de discriminação para a escolha do melhor modelo a ser usado para estimar as volatilidades e fazer previsões de séries financeiras. Um exemplo empírico de aplicação da metodologia é introduzido com a série financeira do IBOVESPA.