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| Schemberger,Elder E.; Fontana,Fabiane S.; Johann,Jerry A.; Souza,Eduardo G. De. |
| ABSTRACT Precision Agriculture (PA) uses technologies with the aim of increasing productivity and reducing the environmental impact by means of site-specific application of agricultural inputs. In order to make it economically feasible, it is essential to improve the current methodologies as well as proposing new ones, in which data regarding productivity, soil, and compound indicators are used to determine Management Areas (MAs). These units are heterogeneous areas within the same region. With these methodologies, data mining (DM) techniques and algorithms may be used. In order to integrate DM techniques to PA, the aim of this study was to associate MAs created for soy productivity using the Fuzzy C-means algorithm by SDUM software over a 9.9-ha plot as... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Algorithms; EM; KDD; K-means; Weka. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000100185 |
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| Lopes,Allan R.; Marcolin,Jonatas; Johann,Jerry A.; Boas,Márcio A. Vilas; Schuelter,Adilson R.. |
| ABSTRACT The aim of this study is to identify homogeneous rainfall zones in the winter and summer 1st and 2nd crops, in the state of Paraná, Brazil. The zones were defined by clustering using the expectation-maximization (EM) algorithm to transform seasonal rainfall series. Monthly average rainfall data collected from 157 weather stations for 20 years (1996 to 2015) were employed. The results show that the number of homogeneous zones varied among growing seasons. The summer crop presented two clusters, with rainfall averages of 1489 and 1925 mm; the second crop presented four clusters, with averages of 1849, 1004, 1454, and 1182 mm; and the winter crop had three clusters, with averages of 969, 1498, and 1171 mm. Clustering was a useful instrument to... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data mining; Clusters; Expectation-maximization; Weka; Soybean; Maize; Wheat. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600707 |
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