|
|
|
Registros recuperados: 54 | |
|
| |
|
|
SILVA, F. C. da; MASSRUHÁ, S. M. F. S.; DEUS, R. S. de; SANTOS, A. D. dos; BARBIERI, V.; CRUZ, S. A. B. da; MALAVOLTA, E.. |
This paper presents a web-based expert system for diagnosis of plant nutrient disorders in sugarcane. This system aims to provide a guide to identification of essential and functional plant nutrient disorders in sugarcane to avoid deficiency and to solve nutritional problems arising from the development of this culture. It is directed toward the sugarcane farmer, research scientist, extension specialist, student, and consultant. The first version of system was developed using the virtual diagnosis framework developed by Embrapa and CENA/USP. The adopted development methodology and the current status of the system for diagnosis of nutritional deficiency in sugarcane are discussed in this paper. The experience acquired in the development of this expert... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Sistema especialista para internet; Deficiência nutricional em cana-de-açúcar; Inteligência artificial; Inferência dedutiva; Sugarcane; Expert systems; Artificial intelligence; Saccharum. |
Ano: 2011 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/897665 |
| |
|
| |
|
| |
|
|
SOUZA, K. X. S. de; OLIVEIRA, S. R. de M.; MACÁRIO, C. G. do N.; ESQUERDO, J. C. D. M.; MOURA, M. F.; LEITE, M. A. de A.; LIMA, H. P. de; CASTRO, A. de; TERNES, S.; YANO, I. H.; SANTOS, E. H. dos. |
Introdução. Tecnologias digitais. Organização, representação e acesso à informação. Modelagem matemática e estatística. Inteligência artificial. Sensores e estudo da terra. Tecnologias convergentes. Considerações finais. |
Tipo: Capítulo em livro científico (ALICE) |
Palavras-chave: Agricultura digital; Tecnologias digitais; Inteligência artificial; Digital agriculture; Agricultura; Agriculture; Artificial intelligence. |
Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126215 |
| |
|
| |
|
|
CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 12., 2019, Indaiatuba.. |
O evento foi composto por painéis, palestras, apresentação de trabalhos científicos, concurso de teses e dissertações, além de um concurso de iniciação científica. Nesta edição, houve também espaço para resumos, na categoria pôster, a fim de propiciar a apresentação de soluções de ferramentas, processos tecnológicos ou resultados parciais de PD&I. |
Tipo: Livro científico (ALICE) |
Palavras-chave: Agroinformática; Agricultura digital; Inteligência artificial; Agricultura. |
Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125706 |
| |
|
| |
|
| |
|
|
CHIARELLO, F.; STEINER, M. T. A.; OLIVEIRA, E. B. de; ARCE, J. E.; FERREIRA, J. C.. |
Artificial Intelligence has been an important support tool in different spheres of activity, enabling knowledge aggregation, process optimization and the application of methodologies capable of solving complex real problems. Despite focusing on a wide range of successful metrics, the Artificial Neural Network (ANN) approach, a technique similar to the central nervous system, has gained notoriety and relevance with regard to the classification of standards, intrinsic parameter estimates, remote sense, data mining and other possibilities. This article aims to conduct a systematic review, involving some bibliometric aspects, to detect the application of ANNs in the field of Forest Engineering, particularly in the prognosis of the essential parameters for... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Bibliometric Review; Multilayer Perceptron; Forest Engineering Problems; Revisão sistemática; Revisão Bibliométrica; Inteligência artificial; Artificial intelligence; Systematic review. |
Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115699 |
| |
|
|
CARVALHO, L. P. de; TEODORO, P. E.; BARROSO, L. M. A.; FARIAS, F. J. C.; MORELLO, C. de L.; NASCIMENTO, M.. |
Fiber length is the main trait that needs to be improved in cotton. However, the presence of genotypes x environments interaction for this trait can hinder the recommendation of genotypes with greater length fibers. The aim of this study was to evaluate the adaptability and stability of the fibers length of cotton genotypes for recommendation to the Midwest and Northeast, using artificial neural networks (ANNs) and Eberhart and Russell method. Seven trials were carried out in the states of Ceará, Rio Grande do Norte, Goiás and Mato Grosso do Sul. Experimental design was a randomized block with four replications. Data were submitted to analysis of adaptability and stability through the Eberhart & Russell and ANNs methodologies. Based on these methods,... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Inteligência artificial; Algodão; Gossypium Hirsutum; Gossypium Hirsutum Marie Galante; Genótipo; Cotton; Artificial intelligence; Genotype-environment interaction. |
Ano: 2018 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1099791 |
| |
|
|
SILVA, G. N.; NASCIMENTO, M.; SANT'ANNA, I. de C.; CRUZ, C. D.; CAIXETA, E. T.; CARNEIRO, P. C. S.; ROSADO, R. D. S.; PESTANA, K. N.; ALMEIDA, D. P. de; OLIVEIRA, M. da S.. |
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, while the... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Inteligência artificial; Predição; Coffea arabica; Hemileia vastatrix; Marcador molecular; Coffea arabica; Hemileia vastatrix; Artificial intelligence; Genetic markers; Prediction. |
Ano: 2017 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/1069618 |
| |
|
|
REIS, P. C. M. dos R.; SOUZA, A. L. de; REIS, L. P.; CARVALHO, A. M. M. L.; FREITAS, L. J. M. de; RÊGO, L. J. S.; LEITE, H. G.. |
Timber from the second cutting cycle may make up the majority of future crop volumetric. However, there are few studies of the physical and mechanical properties of this timber, which are important to support the consolidation of new species. This study aimed to use Artificial Neural Networks to estimate the physical and mechanical properties of wood from the Amazon, based on basic density. The properties were: shrinkage (tangential, radial and volumetric), static bending, parallel and perpendicular to the fiber compression, parallel and transverse to the fibers, Janka hardness, traction, splitting and shear. The estimate followed the tendency of the data observed for the tangential, radial and volumetric shrinkage. The network estimated the mechanical... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Modelagem; Inteligência artificial; Madeira; Tecnologia. |
Ano: 2018 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1095097 |
| |
|
| |
|
| |
|
| |
|
| |
Registros recuperados: 54 | |
|
|
|