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Industrial Brewery Modelling by Using Artificial Neural Network

Assidjo Nogbou, Emmanuel and Yao, B. and Amane, D. and Ado, G. and Azzaro-Pantel, Catherine and Davin, André Industrial Brewery Modelling by Using Artificial Neural Network. (2006) Journal of Applied Science, vol. 6 (n° 8). pp. 1858-1862.

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Official URL: http://ansijournals.com/3/detail.php?id=1&jid=jas&theme=3&issueno=396&articleno=56515

Abstract

Fermentation is a complex phenomenon well studied which still provides challenges to brewers. In this study, artificial neural network, precisely multi layer perceptron and recurrent one were utilised for modelling either static (yeast quantity to add to wort for fermentation) or dynamic (fermentation process) phenomena. In both cases, the simulated responses are very close to the observed ones with residual biases inferior to 4.5%. Thus, ANN models present good predictive ability confirming the suitability of ANN for industrial process modelling.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution: Université de Toulouse > Institut National Polytechnique de Toulouse - INPT
Université de Toulouse > Université Paul Sabatier-Toulouse III - UPS
French research institutions > Centre National de la Recherche Scientifique - CNRS
Other partners > Institut National Polytechnique Felix Houphouët-Boigny - INP-HB (IVORY COAST)
Laboratory name:
Laboratoire de Procédés Industriels de Synthèse et de l' Environnement (Yamoussoukro, Ivory Coast)
Laboratoire de Génie Chimique - LGC (Toulouse, France) - Procédés Systèmes Industriels (PSI) - Conception Optimisation Ordonnancement des Procédés (COOP)
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Deposited By:Hélène Dubernard

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