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| Registros recuperados : 4 | |
| 1. |  | ÁVILA, L. F.; MELLO, C. R. de; YANAGI, S. de N. M.; SACRAMENTO NETO, O. B. Tendências de temperaturas mínimas e máximas do ar no Estado de Minas Gerais. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 4, p. 247-256, abr. 2014. Título em inglês: Trends of minimum and maximum air temperatures in the state of Minas Gerais, Brazil.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 4. | | LOURENÇONI, D.; ABREU, P. G. de; YANAGI JUNIOR, T.; CAMPOS, A. T.; YANAGI, S. de N. M. Pertinence curves in fuzzy modeling of the productive responses of broilers. Revista Engenharia Agrícola, Jaboticabal, v. 39, n. 3, p. 265-271, 2019.| Biblioteca(s): Embrapa Suínos e Aves. |
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| Registros recuperados : 4 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
28/10/2020 |
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Data da última atualização: |
28/10/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
LOURENÇONI, D.; ABREU, P. G. de; YANAGI JUNIOR, T.; CAMPOS, A. T.; YANAGI, S. de N. M. |
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Afiliação: |
DIAN LOURENÇONI, Univasf; PAULO GIOVANNI DE ABREU, CNPSA; TADAYUKI YANAGI JUNIOR, Univasf; ALESSANDRO T. CAMPOS, Univasf; SILVIA DE N. M. YANAGI, Univasf. |
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Título: |
Pertinence curves in fuzzy modeling of the productive responses of broilers. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Revista Engenharia Agrícola, Jaboticabal, v. 39, n. 3, p. 265-271, 2019. |
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DOI: |
http://dx.doi.org/10.1590/1809-4430 |
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Idioma: |
Inglês |
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Conteúdo: |
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 index (PEI). Triangular, trapezoidal, and Gaussian pertinence curves were combined and applied to represent the input and output fuzzy sets, totaling nine fuzzy models for each output variable. The combinations of pertinence curves provided adequate responses for the prediction of AL, GP, RC, and PEI. However, the selection of the types of curves should be studied on a case-by-case basis, so that the smallest possible simulation errors are obtained. |
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Palavras-Chave: |
Sistemas fuzzy. |
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Thesagro: |
Avicultura; Frango de Corte; Modelo Matemático; Produção Animal. |
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Thesaurus NAL: |
Fuzzy logic. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217242/1/final9397.pdf
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Marc: |
LEADER 01991naa a2200253 a 4500
001 2126063
005 2020-10-28
008 2019 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1590/1809-4430$2DOI
100 1 $aLOURENÇONI, D.
245 $aPertinence curves in fuzzy modeling of the productive responses of broilers.$h[electronic resource]
260 $c2019
520 $aAbstract: 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 index (PEI). Triangular, trapezoidal, and Gaussian pertinence curves were combined and applied to represent the input and output fuzzy sets, totaling nine fuzzy models for each output variable. The combinations of pertinence curves provided adequate responses for the prediction of AL, GP, RC, and PEI. However, the selection of the types of curves should be studied on a case-by-case basis, so that the smallest possible simulation errors are obtained.
650 $aFuzzy logic
650 $aAvicultura
650 $aFrango de Corte
650 $aModelo Matemático
650 $aProdução Animal
653 $aSistemas fuzzy
700 1 $aABREU, P. G. de
700 1 $aYANAGI JUNIOR, T.
700 1 $aCAMPOS, A. T.
700 1 $aYANAGI, S. de N. M.
773 $tRevista Engenharia Agrícola, Jaboticabal$gv. 39, n. 3, p. 265-271, 2019.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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