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Registros recuperados: 24 | |
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SCHIKOWSKI,ANA B.; CORTE,ANA P.D.; RUZA,MARIELI S.; SANQUETTA,CARLOS R.; MONTAÑO,RAZER A.N.R.. |
Abstract Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the accuracy of machine learning (ML) techniques in relation to a volumetric model and a taper function for acácia negra. We used cubing data, and fit equations with Schumacher and Hall volumetric model and with Hradetzky taper function, compared to the algorithms: k nearest neighbor (k-NN), Random Forest (RF) and Artificial Neural Networks (ANN) for estimation of total volume and diameter to the relative height. Models were ranked according to error statistics, as well as their dispersion was verified.... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial intelligence; Data mining; Random forest; ANN. |
Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000703389 |
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Lourençoni,Dian; Yanagi Junior,Tadayuki; Yanagi,Silvia de N. M.; Abreu,Paulo G. de; Campos,Alessandro T.. |
ABSTRACT Broiler chickens are homoeothermic animals, i.e., animals capable of maintaining their body temperature within quite narrow limits; therefore, climate change poses a great challenge to poultry. With this in mind, this research aims to evaluate the performance of broilers submitted to different commercial production systems and exposed to different future scenarios, taking into account the climate change trends. To achieve this objective, we developed and validated a fuzzy model able to predict the performance of a broiler as a function of enthalpy along its life stages. This model was developed and validated in part I of this article based on experimental data collected for one year in three aviaries: conventional, negative pressure, and dark... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Broiler industry; Artificial intelligence; Climate change; Fuzzy system. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100011 |
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Lourençoni,Dian; Abreu,Paulo G. de; Yanagi Junior,Tadayuki; Campos,Alessandro T.; Yanagi,Silvia de N. M.. |
ABSTRACT The selection of the type of fuzzy systems pertinence curve allows a better representation of the mathematical model and a smaller simulation error. We aimed to study the effect of pertinence curves in fuzzy modeling of broiler performance, created in different production systems. For the development and testing of fuzzy models, three commercial aviaries (conventional, tunnel with negative pressure, and dark house) were evaluated over one year, totaling six lots per system. For the development of the model, the input variables were enthalpy in each rearing phase (initial: phases 1, 2, and 3; growth: phase 4; and final: phase 5) and the output variables were feed intake (FE), weight gain (GP), feed conversion (FE), and the productive efficiency... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry farming; Production performance; Artificial intelligence; Fuzzy logic. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000300265 |
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Lourençoni,Dian; Yanagi Junior,Tadayuki; Abreu,Paulo G. de; Campos,Alessandro T.; Yanagi,Silvia de N. M.. |
ABSTRACT Broiler chickens are classified as homoeothermic animals and require a production environment within well-defined thermal comfort intervals. Therefore, the development of algorithms (mathematical models) to control the environment that can be embedded in microcontrollers becomes necessary. Hence, this work aimed to develop a fuzzy model for predicting the productive performance of broiler chickens as a function of the thermal environment during the various breeding phases. The Mamdani inference and defuzzification methods were used, by means of the gravity center, to develop the fuzzy model. Two hundred and forty-three rules with weighting factors of 1.0 each were elaborated. Three commercial warehouses (conventional system, wind tunnel with... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry farming; Productive performance; Artificial intelligence; Fuzzy logic. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100001 |
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Abreu,Lucas H. P.; Yanagi Junior,Tadayuki; Bahuti,Marcelo; Hernández-Julio,Yamid F.; Ferraz,Patrícia F. P.. |
ABSTRACT Due to a number of factors involving the thermal environment of a broiler cutting installation and its interaction with the physiological and productive responses of birds, artificial intelligence has been shown to be an interesting methodology to assist in the decision-making process. For this reason, the main aim of this work was to develop an artificial neural network (ANN) to predict feed conversion (FC), water consumption (Cwater), and cloacal temperature (tclo) of broilers submitted to different air dry-bulb temperatures (24, 27, 30, and 33°C) and durations (1, 2, 3, and 4 days) of thermal stress in the second week of the production cycle. Relative humidity and wind speed were fixed at 60% and 0.2 ms−1, respectively. The experimental data... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Poultry; Thermal stress; Artificial intelligence. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100001 |
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Araújo Júnior,Carlos Alberto; Souza,Pábulo Diogo de; Assis,Adriana Leandra de; Cabacinha,Christian Dias; Leite,Helio Garcia; Soares,Carlos Pedro Boechat; Silva,Antonilmar Araújo Lopes da; Castro,Renato Vinícius Oliveira. |
Abstract: The objective of this work was to compare methods of obtaining the site index for eucalyptus (Eucalyptus spp.) stands, as well as to evaluate their impact on the stability of this index in databases with and without outliers. Three methods were tested, using linear regression, quantile regression, and artificial neural network. Twenty-two permanent plots from a continuous forest inventory were used, measured in trees with ages from 23 to 83 months. The outliers were identified using a boxplot graphic. The artificial neural network showed better results than the linear and quantile regressions, both for dominant height and site index estimates. The stability obtained for the site index classification by the artificial neural network was also... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Eucalyptus; Artificial intelligence; Dominant height; Forest inventory; Forest modelling; Non-sampling errors. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103200 |
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Silva,Gabi Nunes; Nascimento,Moysés; Sant’Anna,Isabela de Castro; Cruz,Cosme Damião; Caixeta,Eveline Teixeira; Carneiro,Pedro Crescêncio Souza; Rosado,Renato Domiciano Silva; Pestana,Kátia Nogueira; Almeida,Dênia Pires de; Oliveira,Marciane da Silva. |
Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped,... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Coffea arabica; Hemileia vastatrix; Artificial intelligence; Molecular markers; Prediction. |
Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000300186 |
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Campos, Bráulio Pizziôlo Furtado; Silva, Gilson Fernandes da; Binoti, Daniel Henrique Breda; Mendonça, Adriano Ribeiro de; Leite, Helio Garcia. |
O objetivo deste trabalho foi analisar a capacidade de uma rede neural artificial (RNA) em descrever o perfil do fuste de árvores de diferentes gêneros e espécies em diferentes condições de crescimento. Para fins comparativos, foram ajustadas equações, empregando-se análise de regressão, para descrever o perfil do tronco. Tanto para as redes neurais quanto para as equações de regressão, a avaliação da acurácia foi realizada com base no coeficiente de correlação entre os diâmetros observados e estimados ao longo do fuste, a raiz quadrada do erro quadrático médio percentual (RMSE) e análise gráfica. Os métodos de inteligência artificial, especialmente RNA, podem ser eficazes em descrever o perfil do fuste de árvores de diferentes espécies em diferentes... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Inventário florestal; Modelos de Crescimento e Produção; Estatística Inventário Florestal; Manejo Florestal; Inteligência artificial Forest inventory; Forest management; Artificial intelligence. |
Ano: 2017 |
URL: http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1181 |
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Menezes,Paulo L. de; Azevedo,Carlos A. V. de; Eyng,Eduardo; Dantas Neto,José; Lima,Vera L. A. de. |
ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN) to simulate sprinkler precipitation, using the values of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs)... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Sprinkler; Water distribution uniformity; Artificial intelligence; Computational model. |
Ano: 2015 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662015000900817 |
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Celik,Senol; Eyduran,Ecevit; Karadas,Koksal; Tariq,Mohammad Masood. |
ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: ANN; Artificial intelligence; Data mining; Decision tree; MARS algorithm. |
Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863 |
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Brunassi,Leandro dos Anjos; Moura,Daniella Jorge de; Nääs,Irenilza de Alencar; Vale,Marcos Martinez do; Souza,Silvia Regina Lucas de; Lima,Karla Andrea Oliveira de; Carvalho,Thayla Morandi Ridolfi de; Bueno,Leda Gobbo de Freitas. |
Production losses due to lack of precision in detecting estrus in dairy cows are well known and reported in milk production countries. Nowadays automatic estrus detection has become possible as a result of technical progress in continuously monitoring dairy cows using fuzzy pertinence functions. Dairy cow estrus is usually visually detected; however, solely use of visual detection is considered inefficient. Many studies have been carried out to develop an effective model to interpret the occurrence of estrus and detect estrus; however, most models present too many false-positive alerts and because of this they are sometimes considered unreliable. The objective of this research was to construct a system based on fuzzy inference functions evaluated with a... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Estrus cycle; Artificial intelligence; Expert system. |
Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162010000500002 |
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Registros recuperados: 24 | |
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