A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Heterogeneidade dos componentes de variância na produção de leite e seus efeitos nas estimativas de herdabilidade e repetibilidade

It was evaluated the heterogeneity of components of phenotypic variance and its effects on the heritability and repeatability estimates for milk yield in Holstein cattle. The herds were grouped according to their level of production (low, medium and high) and evaluated in the non-transformed, square-root and logarithmic scale. Variance components were estimated using a restricted maximum likelihood method based on an animal model that included fixed effects of herd-year-season, and as covariates the linear effect of lactation duration and the linear and quadratic effects of cow's age at calving and the random direct additive genetic, permanent environment and residual effects. In the non-transformed scale all the variance components were heterogeneous. on this scale, residual and phenotypic variance components were associated positively with the level of production while in logarithmic scale that association was negative. Estimates of heritability were more affected than the repeatability for the phenotypic variance heterogeneity and their components. The of selection process efficiency for milk production could be affected by the level of production which was considered for genetic parameters estimation.

Measurement of the top-quark mass in t(t)over-bar events with dilepton final states in pp collisions at root s=7 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo das precipitações máximas anuais em Presidente Prudente

Considerando a importância sócio-econômica da região de Presidente Prudente, este estudo teve como objetivo estimar a precipitação pluvial máxima esperada para diferentes níveis de probabilidade e verificar o grau de ajuste dos dados ao modelo Gumbel, com as estimativas dos parâmetros obtidas pelo método de máxima verossimilhança. Pelos resultados, o teste de Kolmogorov-Sminorv (K-S) mostrou que a distribuição Gumbel testada se ajustou com p-valor maior que 0.28 para todos os períodos de tempo considerados, comprovando que a distribuição Gumbel apresenta um bom ajustamento aos dados observados para representar as precipitações pluviais máximas. As estimativas de precipitação obtidas pelo método de máxima verossimilhança são consistentes, conseguindo reproduzir com bastante fidelidade o regime de chuvas da região de Presidente Prudente. Assim, o conhecimento da distribuição da precipitação pluvial máxima mensal e das estimativas das precipitações diárias máximas esperadas, possibilita um planejamento estratégico melhor, minimizando assim o risco de ocorrência de perdas econômicas para essa região.

Hair coat characteristics and sweating rate of Braford cows in Brazil

This paper deals with the effects of hair coat characteristics on the sweating rate of Brazilian Braford cows and estimation of heritabilities and genetic correlations of these traits. Data (n=1607) on hair length, coat thickness, hair diameter, number of hairs per unit area, coat reflectance and sweating rate were recorded from heifers and cows of a commercial herd managed on range under extensive system. The data were analyzed considering the following effects on the model for hair coat traits: classes of sires and contemporary groups; linear effects of month and genotype; linear and quadratic effects of age. The effect of sire was important (P<0.05) for all hair coat traits, except for number of hairs; contemporary groups affected (P<0.05) all hair coat traits; the effect of sampling month was important (P<0.05) for hair length and reflectance; genotype affected (P<0.05) hair length, diameter and coat reflectance; the quadratic effect of age was important (P<0.05) only for coat reflectance. Two models were used to analyze the sweating rate. The first model considered the following fixed effects: classes of contemporary groups and sires; linear effect of genotype, coat thickness, hair length, hair diameter, number of hairs, coat reflectance; linear and quadratic effects of time of day, age, air temperature, partial vapour pressure and radiant heat load. The second model used for the sweating rate considered the same fixed effects for the first model, except that the hair coat characteristics were adjusted for important effects used in the models to analyze hair coat traits. All meteorological factors and contemporary groups were important (P<0.05) on variation of sweating rate in both models. The Restricted Maximum. Likelihood (REML) method was used to estimate variance and covariance components under the sire model. Results included heritability estimates in narrow (h(2)) and broad (H) sense for single-trait analyzes: hair thickness (h(2)=0.16; H-2=0.26); hair length (h(2)=0.18; H-2=0.39); number of hairs (h(2)=0.08 +/- 0.07; H-2=0.08 +/- 0.07); hair diameter (h(2)=0.12 +/- 0.07; H-2=0.12 +/- 0.07); coat reflectance (h(2)=0.30; H-2=0.42); and sweating rate (h(2)=0.10 +/- 0.07; H-2=0.10 +/- 0.07). In general, the genetic correlations between the adaptive traits were favorable as for the direction to select for adaptation in tropical environment; however, they presented high standard errors. The results of this study imply that hair coat characteristics and sweating ability are important for the adaptability to heat stress and they must be better studied and further considered for selection for genetic progress of adaptation in tropical environment. (C) 2007 Elsevier B.V All rights reserved.

The complementary exponential power lifetime model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Constraints implementation for IQML and mode direction-of-arrival estimators

The iterative quadratic maximum likelihood IQML and the method of direction estimation MODE are well known high resolution direction-of-arrival DOA estimation methods. Their solutions lead to an optimization problem with constraints. The usual linear constraint presents a poor performance for certain DOA values. This work proposes a new linear constraint applicable to both DOA methods and compare their performance with two others: unit norm and usual linear constraint. It is shown that the proposed alternative performs better than others constraints. The resulting computational complexity is also investigated.

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Inferência bayesiana na predição de valores genéticos do peso aos 365 dias de bovinos de corte

Data from purebred Simmental, Nellore and Canchim cattle breeds obtained from the respective Brazilian Associations of Breeders were used to estimate variance components and to predict genetic values for 365 days weight. The results obtained by Bayesian inference were compared to those from Restricted Maximum Likelihood (REML) and Best Linear Unbiased Prediction (BLUP), which are the most commonly used methods of estimation and prediction in animal breeding. The two methods presented similar point estimates but the study of the marginal posterior distributions in the Bayesian approach yields more detailed information about the parameters and other unknowns in the model.

Analysis of culling probability in dairy buffalo using survival models

In order to contribute to the genetic breeding programs of buffaloes, this study aimed to determine the influence of environmental effects on the stayability (ST) of dairy female Murrah buffalo in the herd. Data from 1016 buffaloes were used. ST was defined as the ability of the female to remain in the herd for 1, 2, 3, 4, 5 or 6 years after the first calving. Environmental effects were studied by survival analysis, adjusted to the fixed effects of farm, year and season of birth, class of first-lactation milk yield and age at first calving. The data were analyzed using the LIFEREG procedure of the SAS program that fits parametric models to failure time data (culling or ST = 0), and estimates parameters by maximum likelihood estimation. Breeding farm, year of birth and first-lactation milk yield significantly influenced (P < 0.0001) the ST to the specific ages (1 to 6 years after the first calving). Buffaloes that were older at first calving presented higher probabilities of being culled 1 year after the first calving, without any effect on culling at older ages. Buffaloes with a higher milk yield at first calving presented a lower culling probability and remained for a longer period of time in the herd. The effects of breeding farm, year of birth and first-lactation milk yield should be included in models used for the analysis of ST in buffaloes. Copyright © The Animal Consortium 2010.

A bayesian analysis for the parameters of the exponential-logarithmic distribution

The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.

Evolução espaço-temporal do uso e cobertura do solo nas estâncias turísticas de Avaré e Paranapanema, no reservatório de Jurumirim (SP)

Pós-graduação em Geografia - IGCE

Agregação e viés em medidas de diversidade: uma abordagem computacional intensiva

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Papel de polimorfismos genéticos nos genes IL10, TNF e LTA na hanseníase

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Parâmetros genéticos de características de carcaça e de qualidade da carne de aves oriundas de cruzamento recíproco

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)