Artificial neural networks used for the simulation of the batch fermentation bioreactor

Vasile Mircea Cristea, Imre Lucaci Arpad, Şipoş Anca, Brǎtfǎlean Dorina, Paul Şerban Agachi

Research output: Contribution to journalArticlepeer-review


The paper presents the modelling results of the batch alcoholic fermentation bioreactor using both the first principle and the Artificial Neural Networks (ANN) approach. For the nonlinear fermentation process the first principle model validated with experimental data considers for the biomass the Monod and for substrate the Bovée and Strehaiano models, including the temperature influence. It has been used for the ANN model development. A design and training methodology is proposed for statistical modelling based on artificial neural networks. Comparison between the two models is performed revealing the incentives of the ANN modelling method for reducing the computational time and sparing the computer resources.

Original languageEnglish
Pages (from-to)87-94
Number of pages8
JournalStudia Universitatis Babes-Bolyai Chemia
Issue number1
Publication statusPublished - Dec 1 2009

All Science Journal Classification (ASJC) codes

  • Chemistry(all)


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