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Application of artificial neural networks in the prediction of sugarcane juice Pol AGRIAMBI
Coelho,Anderson P.; Bettiol,João V. T.; Dalri,Alexandre B.; Fischer Filho,João A.; Faria,Rogério T. de; Palaretti,Luiz F..
ABSTRACT Innovative techniques that seek to minimize the costs of production and the laboriousness of certain operations are one of the great challenges in the sugar-energy sector nowadays. Thus, the objective of the present study was to estimate the Pol values ​​of sugarcane juice as a function of °Brix and wet cake weight (WCW) using artificial neural network (ANN) modeling. A database was organized consisting of 204 technological analyses from a field experiment with 15 treatments and 2 years of evaluation. 75% of the data were used for the calibration of the model and 25% for its validation. Multilayer Perceptron ANNs were used for calibration and validation of the data. Before calibration, the variables were normalized. The training algorithm used was...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Trs; Brix; Sucrose; Technological quality.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000100009
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