65 resultados para SMOOTHING SPLINE
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Pós-graduação em Ciência da Computação - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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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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OBJETIVO Analisar mudanças espaciais no risco de Aids e a relação entre incidência da doença e variáveis socioeconômicas. MÉTODOS Estudo caso-controle espacial, de base populacional, realizado em Rondônia, Brasil, com 1.780 casos notificados pelo Sistema de Vigilância Epidemiológica e os controles a partir de dados demográficos de 1987 a 2006. Os casos foram agrupados em cinco períodos de cinco anos consecutivos. Um modelo aditivo generalizado foi ajustado aos dados. O status dos indivíduos (caso ou controle) foi considerado como a variável dependente e independente: um alisamento ( spline ) bidimensional das coordenadas geográficas e variáveis socioeconômicas municipais. Os valores observados para o teste Moran I foram comparados com a distribuição de referência dos valores obtidos em condições de aleatoriedade espacial. RESULTADOS O risco de Aids apresentou padrão espacial e temporal marcado. A incidência associou-se a indicadores socioeconômicos municipais, como urbanização e capital humano. As maiores taxas de incidência de Aids ocorreram em municípios ao longo da rodovia BR-364; os resultados do teste Moran I mostram correlação espacial positiva associada à contiguidade dos municípios com a rodovia, no terceiro e quarto períodos (p = 0,05). CONCLUSÕES A incidência da doença foi maior em municípios de maior riqueza econômica e urbanização e naqueles cortados pelas estradas principais de Rondônia. O rápido desenvolvimento associado à ocupação de regiões remotas pode ser acompanhado por aumento de riscos à saúde.
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Phosphorus is one of the limiting nutrients for sugarcane development in Brazilian soils. The spatial variability of this nutrient is great, defined by the properties that control its adsorption and desorption reactions. Spatial estimates to characterize this variability are based on geostatistical interpolation. However, inherent uncertainties in the procedure of these estimates are related to the variability structure of the property under study and the sample configuration of the area. Thus, the assessment of the uncertainty of estimates associated with the spatial distribution of available P (Plabile) is decisive to optimize the use of phosphate fertilizers. The purpose of this study was to evaluate the performance of sequential Gaussian simulation (sGs) and ordinary kriging (OK) in the modeling of uncertainty in available P estimates. A sampling grid with 626 points was established in a 200-ha experimental sugarcane field in Tabapuã, São Paulo State. The sGs algorithm generated 200 realizations. The sGs realizations reproduced the statistics and the distribution of the sample data. The G statistic (0.81) indicated good agreement between the values of simulated and observed fractions. The sGs realizations preserved the spatial variability of Plabile without the smoothing effect of the OK map. The accuracy in the reproduction of the variogram of the sample data obtained by the sGs realizations was on average 240 times higher than that obtained by OK. The uncertainty map, obtained by OK, showed less variation in the study area than that obtained by sGs. Thus, the evaluation of uncertainties by sGs was more informative and can be used to define and delimit specific management areas more precisely.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Engenharia Elétrica - FEB
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Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Given the importance of preserving the water quality of the Guarani Aquifer, the work done in the hydrographic basin of the rivers Jacaré-Guaçú e Jacaré-Pepira, located in the central-northern São Paulo state, was made to map the hydraulic conductivity from the use of some empirical methods associated with granulometric analysis and in situ testing, specifically with the Guelph permeameter. All results were submitted to a correlation analysis and subsequently mapped using the methodology of minimum curvature, based on numerical techniques Spline. These procedures provide for studies of aquifer vulnerability and assist in decision making in environmental projects and guidelines for urban planning
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The continuous advance of the Brazilian economy and increased competition in the heavy equipment market, increasingly point to the need for accurate sales forecasting processes, which allow an optimized strategic planning and therefore better overall results. In this manner, we found that the sales forecasting process deserves to be studied and understood, since it has a key role in corporate strategic planning. Accurate forecasting methods enable direction of companies to circumvent the management difficulties and the variations of finished goods inventory, which make companies more competitive. By analyzing the stages of the sales forecasting it was possible to observe that this process is methodical, bureaucratic and demands a lot of training for their managers and professionals. In this paper we applied the modeling method and the selecting process which has been done for Armstrong to select the most appropriate technique for two products of a heavy equipment industry and it has been through this method that the triple exponential smoothing technique has been chosen for both products. The results obtained by prediction with the triple exponential smoothing technique were better than forecasts prepared by the industry experts
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Pós-graduação em Engenharia Elétrica - FEB