Classification of the initial development of eucaliptus using data mining techniques.
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262 |
Resumo: | Abstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature. |
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Classification of the initial development of eucaliptus using data mining techniques.Mineração de dadosEucaliptoEucalyptusTechnologyAbstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature.ELIZEU DE SOUZA LIMA, Unicamp; ZIGOMAR MENEZES DE SOUZA, USP, Jaboticabal; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LENON HENRIQUE LOVERA, Unicamp; CAMILA VIANA VIEIRA FARHATE, Unicamp.LIMA, E. de S.SOUZA, Z. M. deOLIVEIRA, S. R. de M.LOVERA, L. H.FARHATE, C. V. V.2017-07-07T11:11:11Z2017-07-07T11:11:11Z2017-07-0720172018-02-28T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCerne, v. 23, n. 2, p. 201-208, 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/107226210.1590/01047760201723022296enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T04:35:11Zoai:www.alice.cnptia.embrapa.br:doc/1072262Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T04:35:11Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Classification of the initial development of eucaliptus using data mining techniques. |
title |
Classification of the initial development of eucaliptus using data mining techniques. |
spellingShingle |
Classification of the initial development of eucaliptus using data mining techniques. LIMA, E. de S. Mineração de dados Eucalipto Eucalyptus Technology |
title_short |
Classification of the initial development of eucaliptus using data mining techniques. |
title_full |
Classification of the initial development of eucaliptus using data mining techniques. |
title_fullStr |
Classification of the initial development of eucaliptus using data mining techniques. |
title_full_unstemmed |
Classification of the initial development of eucaliptus using data mining techniques. |
title_sort |
Classification of the initial development of eucaliptus using data mining techniques. |
author |
LIMA, E. de S. |
author_facet |
LIMA, E. de S. SOUZA, Z. M. de OLIVEIRA, S. R. de M. LOVERA, L. H. FARHATE, C. V. V. |
author_role |
author |
author2 |
SOUZA, Z. M. de OLIVEIRA, S. R. de M. LOVERA, L. H. FARHATE, C. V. V. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
ELIZEU DE SOUZA LIMA, Unicamp; ZIGOMAR MENEZES DE SOUZA, USP, Jaboticabal; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LENON HENRIQUE LOVERA, Unicamp; CAMILA VIANA VIEIRA FARHATE, Unicamp. |
dc.contributor.author.fl_str_mv |
LIMA, E. de S. SOUZA, Z. M. de OLIVEIRA, S. R. de M. LOVERA, L. H. FARHATE, C. V. V. |
dc.subject.por.fl_str_mv |
Mineração de dados Eucalipto Eucalyptus Technology |
topic |
Mineração de dados Eucalipto Eucalyptus Technology |
description |
Abstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-07-07T11:11:11Z 2017-07-07T11:11:11Z 2017-07-07 2017 2018-02-28T11:11:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Cerne, v. 23, n. 2, p. 201-208, 2017. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262 10.1590/01047760201723022296 |
identifier_str_mv |
Cerne, v. 23, n. 2, p. 201-208, 2017. 10.1590/01047760201723022296 |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1822721270840557568 |