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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/05/2012 |
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Data da última atualização: |
04/06/2012 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MASSRUHA, S. M. F. S.; RICCIOTI, R. F.; LIMA, H. P. de; MEIRA, C. A. A. |
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Afiliação: |
SILVIA MARIA FONSECA S MASSRUHA, CNPTIA; RAPHAEL FUINI RICCIOTI, Estagiário CNPTIA; HELANO POVOAS DE LIMA, CNPTIA; CARLOS ALBERTO ALVES MEIRA, CNPTIA. |
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Título: |
DiagData: A Tool for Generation of Fuzzy Inference System. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Journal of Environmental Science and Engineering B, p. 336-343, 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, providing a reduction of time. MenosAbstract: In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, pro... Mostrar Tudo |
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Palavras-Chave: |
Árvore de decisão; Fuzzy; Mineração de dados; Modelagem; Sistema de inferência fuzzy. |
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Thesaurus Nal: |
Models. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 1923931
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100 1 $aMASSRUHA, S. M. F. S.
245 $aDiagData$bA Tool for Generation of Fuzzy Inference System.$h[electronic resource]
260 $c2012
520 $aAbstract: In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, providing a reduction of time.
650 $aModels
653 $aÁrvore de decisão
653 $aFuzzy
653 $aMineração de dados
653 $aModelagem
653 $aSistema de inferência fuzzy
700 1 $aRICCIOTI, R. F.
700 1 $aLIMA, H. P. de
700 1 $aMEIRA, C. A. A.
773 $tJournal of Environmental Science and Engineering B, p. 336-343, 2012.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| 5. |  | MENDONÇA, F. S.; MACNEIL, M. D.; NALERIO, E. S.; CARDOSO, L. L.; GIONGO, C.; CARDOSO, F. F. Breed direct, maternal and heteros is effects due to Angus, Caracu, Hereford and Nelore on carcass and meat quality traits of cull cows. Livestock Science, v. 243, 104374, Jan. 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 6. | | MENDONÇA, F. S.; MACNEIL, M. D.; LEAL, W. S.; AZAMBUJA, R. C. C.; RODRIGUES, P. F.; CARDOSO, F. F. Crossbreeding effects on growth and efficiency in beef cow-calf systems: evaluation of Angus, Caracu, Hereford and Nelore breed direct, maternal and heterosis effects. Translational Animal Science, v. 3, n. 4, p. 1286-1295, July 2019.| Tipo: Artigo em Periódico Indexado |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 8. | | YOKOO, M. J. I.; SIMÕES, M. da R. S.; JUNQUEIRA, V. S.; MINHO, A. P.; GULIAS GOMES, C. C.; MACNEIL, M. D.; CARDOSO, F. F. Economic value for the trait tick count in Brangus cattle. In: INTERNATIONAL MEETING OF ADVANCES IN ANIMAL SCIENCE, 2016, Jaboticabal. Papers... Jaboticabal: Unesp, 2016. IMAS. Pôster 45209.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 9. | | PORTES, J, V.; MENEZES, G. R. de O.; SILVA, L. O. C. da; MACNEIL, M. D.; ABREU, U. G. P. de; LACERDA, V. V. de; BRACCINI NETO, J. Selection indexes for nellore production system in the Brazilian Pantanal. Revista Brasileira de Zootecnia, v.50, e20200264, 2021. Animal production systems and agribusiness.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Gado de Corte; Embrapa Pantanal. |
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| 10. | | CARDOSO, L. L.; TAROUCO, J. U.; MACNEIL, M. D.; LOBATO, J. F. P.; DAMBRÓS, M. C.; FREITAS, A. K. de; DEVICENZI, T.; FEIJÓ, F. D.; CARDOSO, F. F. Sample size and prediction of weight and yield of individual cuts from Braford steers pistol hindquarters. Scientia Agricola, v. 77, n. 4, e20180224, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| 11. | | SIMÕES, M. R. S.; LEAL, J. J. B.; MINHO, A. P.; GULIAS GOMES, C. C.; MACNEIL, M. D.; COSTA, R. F.; JUNQUEIRA, V. S.; SCHMIDT, P. I.; CARDOSO, F. F.; BOLIGON, A. A.; YOKOO, M. J. I. Breeding objectives of Brangus cattle in Brazil. Journal of Animal Breeding Genetics, v. 37, n. 2, p. 177-188, Mar. 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 12. | | SIMÕES, M. R. S.; LEAL, J. J. B.; MINHO, A. P.; GULIAS GOMES, C. C.; MACNEIL, M. D.; COSTA, R. F.; JUNQUEIRA, V. S.; SCHMIDT, P. I.; CARDOSO, F. F.; BOLIGON, A. A.; YOKOO, M. J. I. Breeding objectives of Brangus cattle in Brazil. Journal of Animal Breeding and Genetics, v. 137, n. 2, p. 177-188, Mar. 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Pecuária Sul. |
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| Registros recuperados : 12 | |
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