Neural Model for the Prediction of Volume Losses in the Aging Process of Rums

Modelo neuronal para la predicción de mermas en el proceso de añejamiento de rones

Main Article Content

Beatriz García-Castellanos
Osney Pérez-Ones, Ph. D.
Lourdes Zumalacárregui-de-Cárdenas, Ph. D.
Idania Blanco-Carvajal, M.Sc.
Luis Eduardo López-de-la-Maza

Abstract

The rum aging process shows volume losses, called wastage. The numerical operation variables: product, boardwalk, horizontal and vertical positions, date, volume, alcoholic degree, temperature, humidity and aging time, recorded in databases, contain valuable information to study the process. MATLAB 2017 software was used to estimate volume losses. In the modeling of the rum aging process, the multilayer perceptron neuronal network with one and two hidden layers was used, varying the number of neurons in these between 4 and 10. The Levenberg-Marquadt (LM) and Bayesian training algorithms were compared (Bay) The increase in 6 consecutive iterations of the validation error and 1,000 as the maximum number of training cycles were the criteria used to stop the training. The input variables to the network were: numerical month, volume, temperature, humidity, initial alcoholic degree and aging time, while the output variable was wastage. 546 pairs of input/output data were processed. The statistical Friedman and Wilcoxon tests were performed to select the best neural architecture according to the mean square error (MSE) criteria. The selected topology has a 6-4-4-1 structure, with an MSE of 2.1∙10-3 and a correlation factor (R) with experimental data of 0.9898. The neural network obtained was used to simulate thirteen initial aging conditions that were not used for training and validation, detecting a coefficient of determination (R2) of 0.9961.

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Article Details

Author Biographies (SEE)

Beatriz García-Castellanos, Instituto Cubano de Investigaciones de los Derivados de la Caña de Azúcar

Ingeniera Química

Centro de Referencia de Alcoholes y Bebidas (CERALBE)

Osney Pérez-Ones, Ph. D., Universidad Tecnológica de La Habana “José Antonio Echeverría”

Profesor Auxiliar

Decano

Facultad de Ingeniería Química

Lourdes Zumalacárregui-de-Cárdenas, Ph. D., Universidad Tecnológica de La Habana “José Antonio Echeverría”

Profesor Titular

Facultad de Ingeniería Química

Idania Blanco-Carvajal, M.Sc., Instituto Cubano de Investigaciones de los Derivados de la Caña de Azúcar

Investigador Auxiliar

Jefe de Producción

Centro de Referencia de Alcoholes y Bebidas (CERALBE)

Luis Eduardo López-de-la-Maza, Universidad Tecnológica de La Habana “José Antonio Echeverría”

Profesor Instructor

Facultad de Ingeniería Química

References (SEE)

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