866 resultados para Ordinary Least Squares Method
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Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.
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Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.
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GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and / or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.
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The objective of this paper is to show a methodology to estimate transmission line parameters. The method is applied in a single-phase transmission line using the method of least squares. In this method the longitudinal and transversal parameters of the line are obtained as a function of a set of measurements of currents and voltages (as well as their derivatives with respect to time) at the terminals of the line during the occurrence of a short-circuit phase-ground near the load. The method is based on the assumption that a transmission line can be represented by a single circuit π. The results show that the precision of the method depends on the length of the line, where it has a better performance for short lines and medium length. © 2012 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Engenharia Elétrica - FEIS
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Includes bibliography.
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Pós-graduação em Engenharia Elétrica - FEIS
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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O presente trabalho propõe metodologias para detectar a presença e localizar um intruso em ambientes indoor, 2-D e 3-D, sendo que neste último, utiliza-se um sistema cooperativo de antenas e, em ambos os casos, o sistema é baseado em radares multiestáticos. Para obter uma alta resolução, o radar opera com pulsos UWB, que possuem amplitude espectral máxima em 1 GHz para ambientes 2-D e, pulsos de banda larga com frequências entre 200 MHz e 500 MHz para ambientes 3-D. A estimativa de localização, para os ambientes bidimensionais, é feita pela técnica de otimização Enxame de Partículas - PSO (Particle Swarm Optimization), pelo método de Newton com eliminação de Gauss e pelo método dos mínimos quadrados com eliminação de Gauss. Para o ambiente tridimensional, foi desenvolvida uma metodologia vetorial que estima uma possível região de localização do intruso. Para a simulação das ondas eletromagnéticas se utiliza o método numérico FDTD (Diferenças Finitas no Domínio do Tempo) associado à técnica de absorção UPML (Uniaxial Perfectly Matched Layer) com o objetivo de truncar o domínio de análise simulando uma propagação ao infinito. Para a análise do ambiente em 2-D foi desenvolvido o ACOR-UWB-2-D e para o ambiente 3-D foi utilizado o software LANE SAGS.
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Neste trabalho serão apresentados os resultados da avaliação experimental de uma metodologia de controle digital preditivo auto-ajustavel aplicada ao controle de tensão de um sistema de geração de energia de escala reduzida. Um estimador recursivo baseado no conhecido método de mínimos quadrados é utilizado na etapa de identificação do controlador preditivo proposto. A etapa de cálculo da lei de controle é realizada com o algoritmo Generalized Predictive Controller (GPC). A avaliação experimental foi realizada com testes de resposta ao degrau e rastreamento aplicados em diferentes condições operacionais do sistema de potência estudado. Para fins de comparação, também serão apresentados os resultados da avaliação de um controlador auto-ajustável que utiliza o método de alocação de pólos para a síntese do sinal de controle e três controladores digitais com parâmetros fixos.