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Registros recuperados: 8
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An artificial neural network model for prediction of quality characteristics of apples during convective dehydration Ciênc. Tecnol. Aliment.
Scala,Karina Di; Meschino,Gustavo; Vega-gálvez,Antonio; Lemus-mondaca,Roberto; Roura,Sara; Mascheroni,Rodolfo.
In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.
Tipo: Info:eu-repo/semantics/article Palavras-chave: Artificial neural networks; Quality attributes; Genetic algorithm; Process optimization; Dried apple.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612013000300004
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Analysis of batch and repeated fedbatch productions of Candida utilis cell mass using mathematical modeling method Electron. J. Biotechnol.
Lin,Yutian; Liu,Guoli; Lin,Huibin; Gao,Ling; Lin,Jianqiang.
Background: Candida utilis is widely used in bioindustry, and its cell mass needs to be produced in a cost effective way. Process optimization based on the experimental results is the major way to reduce the production cost. However, this process is expensive, time consuming and labor intensive. Mathematical modeling is a useful tool for process analysis and optimization. Furthermore, sufficient information can be obtained with fewer experiments by using the mathematical modeling, and some results can be predicted even without doing experiments. Results: In the present study, we performed the mathematical modeling and simulation for the cell mass production of Candida utilis based on limited batch and repeated fedbatch experiments. The model parameters...
Tipo: Journal article Palavras-chave: Candida utilis; Fermentation; Genetic algorithm; Mathematical model.
Ano: 2013 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582013000400002
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Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms Ciencia e Investigación Agraria
Ferreira Neto,José Ambrósio; Carneiro dos Santos Junior,Edgard; Fra Paleo,Urbano; Miranda Barros,David; César de Oliveira Moreira,Mayron.
The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot's productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual...
Tipo: Journal article Palavras-chave: Agrarian reform; Genetic algorithm; Rural settlement; Spatial planning.
Ano: 2011 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202011000200001
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Parameter estimation of a demand forecasting function associated with behavior of weed using genetic algorithm. Repositório Alice
STERZO, M. S.; CRUVINEL, P. E..
bitstream/item/166269/1/PROCI-17-Parameter-estimation-of-a-demand.pdf
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Weed; Genetic algorithm; Estimation of parameters.
Ano: 2017 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1069360
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Predicción de puntos de calor como precursores de incendios forestales Colegio de Postgraduados
González Ramos, Adalberto.
Con el propósito de determinar la relación entre factores humanos y factores geográficos con la presencia de puntos de calor que pudieran constituir posibles incendios forestales, se definió una metodología para evaluar tres tipos de arquitecturas de redes neuronales backpropagation, empleándose como datos de entrada cuatro modelos que resultaron de combinar seis factores humanos con siete factores geográficos. Como datos de salida se usaron los puntos de calor detectados en el territorio que comprende las zonas susceptibles a incendios forestales del Estado de México durante el período del año 2000 al 2005 para las etapas de entrenamiento y prueba. Asimismo, datos del año 2006 se destinaron para la comprobación del funcionamiento de la red. Se usó...
Tipo: Tesis Palavras-chave: Algoritmos genéticos; Redes neuronales retroalimentadas; Predicción de incendios forestales; Modelación; Puntos de calor; Maestría; Forestal; Genetic algorithm; Backpropagation neural nets; Wilfires prediction; Modeling; Fire points.
Ano: 2008 URL: http://hdl.handle.net/10521/1652
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REDUCTION OF SAMPLE SIZE IN THE ANALYSIS OF SPATIAL VARIABILITY OF NONSTATIONARY SOIL CHEMICAL ATTRIBUTES REA
Maltauro,Tamara C.; Guedes,Luciana P. C.; Uribe-Opazo,Miguel A..
ABSTRACT In the study of spatial variability of soil attributes, it is essential to define a sampling plan with adequate sample size. This study aimed to evaluate, through simulated data, the influence of parameters of the geostatistical model and sampling configuration on the optimization process, and resize and reduce the sample size of a sampling configuration of a commercial area composed of 102 points. For this, an optimization process called genetic algorithm (GA) was used to optimize the efficiency of the geostatistical model estimation based on the Fisher information matrix. The simulated data evidenced that the variation of the nugget effect or practical range did not significantly alter the sample size. GA was efficient in reducing the sample...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Fisher information matrix; Genetic algorithm; Geostatistics; Spatial dependence.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000800056
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Research and Applications of Shop Scheduling Based on Genetic Algorithms BABT
ZHAO,Hang; KONG,Fansen.
ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Shop scheduling; Genetic algorithm; Local minimization; Cyclic search.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132016000200601
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Research on manufacturing text classification based on improved genetic algorithm BABT
Kaijun,Zhou; Yifei,Tong.
ABSTRACT According to the features of texts, a text classification model is proposed. Base on this model, an optimized objective function is designed by utilizing the occurrence frequency of each feature in each category. According to the relation matrix oftext resource and features, an improved genetic algorithm is adopted for solution with integral matrix crossover, transposition and recombination of entire population. At last the sample date of manufacturing text information from professional resources database system is taken as an example to illustrate the proposed model and solution for feature dimension reduction and text classification. The crossover and mutation probabilities of algorithm are compared vertically and horizontally to determine a...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Text classification; Genetic algorithm; Dimension reduction; Text classification; Manufacturing text.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132016000200600
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