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| Registros recuperados: 64 | |
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| Dornelles,Eldair F.; Kraisig,Adriana R.; Silva,José A. G. da; Sawicki,Sandro; Roos-Frantz,Fabricia; Carbonera,Roberto. |
| ABSTRACT Artificial intelligence may represent an efficient strategy for simulation and optimization of important processes in agriculture. The main goal of the study is to propose the use of artificial intelligence, namely artificial neural networks and genetic algorithms, respectively, in the simulation of oat grain yield and optimization of seeding density, considering the main succession systems of southern Brazil. The study was conducted in a randomized complete block design with four replicates, following a 4 x 2 factorial scheme, for seeding densities (100, 300, 600 and 900 seeds m-2) and oat cultivars (Brisasul and... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Avena sativa; Artificial neural networks; Genetic algorithms; Innovation. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000300183 |
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| Pereira,Tonismar dos S.; Robaina,Adroaldo D.; Peiter,Marcia X.; Torres,Rogerio R.; Bruning,Jhosefe. |
| ABSTRACT The aim of this study was to present and to evaluate methodologies for the estimation of soil resistance to penetration (RP) using artificial intelligence prediction techniques. In order to do so, a data base with values of physical-water characteristics of the soils available in the literature was used, and the performances of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were evaluated. The models generated from the ANNs were implemented through the multilayer perceptron with backpropagation algorithm of Matlab software, varying the number of neurons in the input and intermediate layers. For the procedure from SVM, the RapidMiner software was used, varying... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil compaction; Machine learning; Support vector machines; Artificial neural networks. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100142 |
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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... |
| 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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| Ferraz,Patricia Ferreira Ponciano; Yanagi Junior,Tadayuki; Hernández Julio,Yamid Fabián; Castro,Jaqueline de Oliveira; Gates,Richard Stephen; Reis,Gregory Murad; Campos,Alessandro Torres. |
| The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Animal welfare; Artificial neural network; Broiler; Modeling; Neuro-fuzzy network; Thermal comfort. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2014000700559 |
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| Alexandridis, Konstantinos T.; Pijanowski, Bryan C.. |
| The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Environmental Economics and Policy. |
| Ano: 2002 |
URL: http://purl.umn.edu/11549 |
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| Brazil leads the way in terms of digitalization in agriculture, and, according to studies conducted by McKinsey, in 2019, the Brazilian agriculturists were, in average, the heaviest users of digital media for their transactions. During the covid-19 pandemic, in 2020, Brazil has grown 10 percentage points, moving from 36% to 46% of agriculturists who use some digital media, surpassing American and European producers who presented a usage rate of 31% and 22%, respectively. The growth of digitalization in agriculture places our country in a distinguished position that can facilitate competitiveness and the future of the agriculture and livestock industry, bringing new tools and approaches to the diversity of Brazilian agriculture and food systems, which have... |
| Tipo: Livros |
Palavras-chave: Agtechs; Agribusiness; Innovation adoption. |
| Ano: 2022 |
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1143152 |
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| Campos, Bráulio Pizziôlo Furtado; Silva, Gilson Fernandes da; Binoti, Daniel Henrique Breda; Mendonça, Adriano Ribeiro de; Leite, Helio Garcia. |
| The objective of this study was to analyze the ability of an artificial neural network (ANN) to describe the stem profile of trees of different genera and species in different growing conditions. For comparative purposes, equations were fit, using regression analysis to describe the stem profile. For neural network as well as for the regression equations, evaluation of accuracy was based on correlation coefficient between observed and estimated diameters along the stem, square root of the mean square percentage error (RMSE) and graphical analysis. Artificial intelligence methods, especially ANN, can be effective in describing trees bole profile of different species in different growth... |
| 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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| 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; 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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| Registros recuperados: 64 | |
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