864 resultados para Genetic Algorithms and Simulated Annealing
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Os algoritmos baseados no paradigma Simulated Annealing e suas variações são atualmente usados de forma ampla na resolução de problemas de otimização de larga escala. Esta popularidade é resultado da estrutura extremamente simples e aparentemente universal dos algoritmos, da aplicabilidade geral e da habilidade de fornecer soluções bastante próximas da ótima. No início da década de 80, Kirkpatrick e outros apresentaram uma proposta de utilização dos conceitos de annealing (resfriamento lento e controlado de sólidos) em otimização combinatória. Esta proposta considera a forte analogia entre o processo físico de annealing e a resolução de problemas grandes de otimização combinatória. Simulated Annealing (SA) é um denominação genérica para os algoritmos desenvolvidos com base nesta proposta. Estes algoritmos combinam técnicas de busca local e de randomização. O objetivo do presente trabalho é proporcionar um entendimento das características do Simulated Annealing e facilitar o desenvolvimento de algoritmos com estas características. Assim, é apresentado como Simulated Annealing e suas variações estão sendo utilizados na resolução de problemas de otimização combinatória, proposta uma formalização através de um método de desenvolvimento de algoritmos e analisados aspectos de complexidade. O método de desenvolvimento especifica um programa abstrato para um algoritmo Simulated Annealing seqüencial, identifica funções e predicados que constituem os procedimentos deste programa abstrato e estabelece axiomas que permitem a visualização das propriedades que estes procedimentos devem satisfazer. A complexidade do Simulated Annealing é analisada a partir do programa abstrato desenvolvido e de seus principais procedimentos, permitindo o estabelecimento de uma equação genérica para a complexidade. Esta equação genérica é aplicável aos algoritmos desenvolvidos com base no método proposto. Uma prova de correção é apresentada para o programa abstrato e um código exemplo é analisado com relação aos axiomas estabelecidos. O estabelecimento de axiomas tem como propósito definir uma semântica para o algoritmo, o que permite a um desenvolvedor analisar a correção do código especificado para um algoritmo levando em consideração estes axiomas. O trabalho foi realizado a partir de um estudo introdutório de otimização combinatória, de técnicas de resolução de problemas, de um levantamento histórico do uso do Simulated Annealing, das variações em torno do modelo e de embasamentos matemáticos documentados. Isto permitiu identificar as características essenciais dos algoritmos baseados no paradigma, analisar os aspectos relacionados com estas características, como as diferentes formas de realizar uma prescrição de resfriamento e percorrer um espaço de soluções, e construir a fundamentação teórica genérica proposta.
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The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.
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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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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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O objetivo deste trabalho foi a caracterização genética de quatro novas estirpes de Rhizobium e a avaliação de sua capacidade de fixação de N2 e nodulação, comparadas a estirpes comerciais e à população nativa de rizóbios de um Latossolo Vermelho. Dois experimentos foram conduzidos em blocos ao acaso, em casa de vegetação. No primeiro experimento, conduzido em tubetes com vermiculita, avaliaram-se a nodulação e a capacidade de fixação das novas estirpes, em comparação com as estirpes comerciais CIAT-899 e PRF-81 e com a população nativa do solo. Das colônias puras isoladas, extraiu-se o DNA genômico e realizou-se o seqüenciamento do espaço intergênico, para a caracterização genética das estirpes e da população nativa de rizóbios. O segundo experimento foi realizado em vasos com solo, para determinação da produtividade e da nodulação do feijoeiro, cultivar Pérola, com o uso das estirpes isoladamente ou em mistura com a PRF-81. A população nativa do solo foi identificada como Rhizobium sp. e se mostrou ineficiente na fixação de nitrogênio. Foram encontradas três espécies de Rhizobium entre as quatro novas estirpes. As estirpes LBMP-4BR e LBMP-12BR estão entre as que têm maior capacidade de nodulação e fixação de N2, e apresentam respostas diferenciadas quando misturadas à PRF-81.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Carcass and meat quality traits of thirty-six feedlot beef heifers from different genetic groups (GG) fed at two concentrate levels (CL) were evaluated using 12- Nellore (NE), 12 - 1/2Angus x 1/2Nellore (AN) and 12 - 1/2Simmental x 1/2Nellore (SN) animals. Six heifers of each GG were randomly assigned into one of two treatments: concentrate at 0.8% or 1.2% of body weight (BW). Heifers fed concentrate at 0.8% of BW had greater (P<0.05) dressing percentage. None of the proximate analysis components of the beef were affected (P>0.05) by either CL or GG. Heifers from the AN group had higher (P<0.05) carcass weights, 12th rib fat thickness and lower dressing percentage (P<0.05) compared to the other groups. NE heifers had greater WBSF values (P<0.05) than the other genetic groups. Data suggest that the concentrate level can be reduced without compromising meat quality traits. (C) 2011 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 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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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
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The objectives of the current study were to investigate the additive genetic associations between heifer pregnancy at 16 months of age (HP16) and age at first calving (AFC) with weight gain from birth to weaning (WG), yearling weight (YW) and mature weight (MW), in order to verify the possibility of using the traits measured directly in females as selection criteria for the genetic improvement of sexual precocity in Nelore cattle. (Co)variance components were estimated by Bayesian inference using a linear animal model for AFC, WG, YW and MW and a nonlinear (threshold) animal model for HP16. The posterior means of direct heritability estimates were: 0.45 +/- 0.02; 0.10 +/- 0.01; 023 +/- 0.02; 0.36 +/- 0.01 and 0.39 +/- 0.04, for HP16, AFC, WG, YW and MW, respectively. Maternal heritability estimate for WG was 0.07 +/- 0.01. Genetic correlations estimated between HP16 and WG, YW and MW were 0.19 +/- 0.04; 0.25 +/- 0.06 and 0.14 +/- 0.05, respectively. The genetic correlations of AFC with WG, YW and MW were low to moderate and negative, with values of -0.18 +/- 0.06; -0.22 +/- 0.05 and -0.12 +/- 0.05, respectively. The high heritability estimated for HP16 suggests that this trait seem to be a better selection criterion for females sexual precocity than AFC. Long-term selection for animals that are heavier at young ages tends to improve the heifers sexual precocity evaluated by HP16 or AFC. Predicted breeding values for HP16 can be used to select bulls and it can lead to an improvement in sexual precocity. The inclusion of HP16 in a selection index will result in small or no response for females mature weight. (C) 2011 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)