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Provedor de dados:  Repositório Alice
País:  Brazil
Título:  Classification of soil respiration in areas of sugarcane renewal using decision tree.
Autores:  FARHATE, C. V. V.
SOUZA, Z. M. de
OLIVEIRA, S. R. de M.
CARVALHO, J. L. N.
LA SCALA JÚNIOR, N.
SANTOS, A. P. G.
Data:  2019-02-13
Ano:  2018
Palavras-chave:  Mineração de dados
Emissão de gás carbônico no solo
Seleção de variável
Temperatura no solo
Matéria orgânica no solo
Árvore de decisão
Data mining
Variable selection
Decision tree
Respiração do Solo
Carbon dioxide
Soil temperature
Soil organic matter
Resumo:  ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soil moisture > potential acidity.

bitstream/item/192660/1/AP-Classification-soil-Farhate.pdf
Tipo:  Artigo em periódico indexado (ALICE)
Idioma:  Inglês
Identificador:  20031

http://www.alice.cnptia.embrapa.br/alice/handle/doc/1105884

http://dx.doi.org/10.1590/1678-992X-2016-0473
Editor:  Scientia Agricola, v. 75, n. 3, p. 216-224, May/June 2018.
Relação:  Embrapa Informática Agropecuária - Artigo em periódico indexado (ALICE)
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