| |
|
|
| Registros recuperados : 96 | |
| Registros recuperados : 96 | |
|
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Unidades Centrais. |
|
Data corrente: |
04/01/2011 |
|
Data da última atualização: |
12/01/2011 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
B - 3 |
|
Autoria: |
PRADO, H. A. do; FERNEDA, E.; FARIA, R. C. de. |
|
Afiliação: |
HERCULES ANTONIO DO PRADO, SGE; EDINILSON FERNEDA, UCB; RICARDO COELHO DE FARIA, UCB. |
|
Título: |
A reasoning-based strategy for exploring the synergy among alternative crops. |
|
Ano de publicação: |
2010 |
|
Fonte/Imprenta: |
Lecture Notes in Computer Science, Heidelberg, v. 6278, p. 174-181. 2010. |
|
Idioma: |
Inglês |
|
Conteúdo: |
This paper focuses on the problem of choosing one among many alternatives, each one expressed as a combination of factors. The problem is approached with a reasoning-based strategy that takes into account the relations among the alternatives discovered by means of a data mining technique. The problem of choosing a combination of different vegetables based on the synergistic effects of the combination and considering some socioeconomic variables is taken as a case study. The idea is to identify combinations that lead to gains in productivity, profitability, and lower costs. Experts recognize that some combinations of cultures can generate synergistic effects that can lead to profits or losses, depending on the production variables involved. However, the analysis of the results of the cultivation of multiple varieties involves a space of possibilities whose treatment is not trivial. Among the alternatives available, this study explored the Combinatorial Neural Model (CNM) that assures the hypotheses generation for all possible combinations, within limits defined by the model parameters. The study was carried out on data collected from farms in the Brazilian Federal District. Two approaches to the problem are presented: (i) the first one based on univariate and bi-dimensional data analysis and (ii) a multidimensional analysis based on the CNM results. |
|
Palavras-Chave: |
Data mining; Mineração de dados; Sistema agrícola. |
|
Thesaurus NAL: |
Farming systems. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 01960naa a2200193 a 4500
001 1871528
005 2011-01-12
008 2010 bl uuuu u00u1 u #d
100 1 $aPRADO, H. A. do
245 $aA reasoning-based strategy for exploring the synergy among alternative crops.$h[electronic resource]
260 $c2010
520 $aThis paper focuses on the problem of choosing one among many alternatives, each one expressed as a combination of factors. The problem is approached with a reasoning-based strategy that takes into account the relations among the alternatives discovered by means of a data mining technique. The problem of choosing a combination of different vegetables based on the synergistic effects of the combination and considering some socioeconomic variables is taken as a case study. The idea is to identify combinations that lead to gains in productivity, profitability, and lower costs. Experts recognize that some combinations of cultures can generate synergistic effects that can lead to profits or losses, depending on the production variables involved. However, the analysis of the results of the cultivation of multiple varieties involves a space of possibilities whose treatment is not trivial. Among the alternatives available, this study explored the Combinatorial Neural Model (CNM) that assures the hypotheses generation for all possible combinations, within limits defined by the model parameters. The study was carried out on data collected from farms in the Brazilian Federal District. Two approaches to the problem are presented: (i) the first one based on univariate and bi-dimensional data analysis and (ii) a multidimensional analysis based on the CNM results.
650 $aFarming systems
653 $aData mining
653 $aMineração de dados
653 $aSistema agrícola
700 1 $aFERNEDA, E.
700 1 $aFARIA, R. C. de
773 $tLecture Notes in Computer Science, Heidelberg$gv. 6278, p. 174-181. 2010.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
