ARTIFICIAL NEURAL NETWORKS USED FOR THE SIMULATION OF THE BATCH FERMENTATION BIOREACTOR

Journal article

Authors/Editors

Agachi, Paul

Research Areas

No matching items found.

Publication Details

Author list: Cristea VM, Arpad IL, Anca S, Dorina B, Agachi PS

Publisher: UNIV ATHENS FIRST DEPT OBSTETR

Place: CLUJ-NAPOCA

Publication year: 2009

Journal acronym: STUD U BABES-BOL CHE

Volume number: 54

Issue number: 4

Start page: 87

End page: 94

Number of pages: 8

ISSN: 1224-7154

Languages: English-Great Britain (EN-GB)

View in Web of Science | View citing articles in Web of Science

Abstract

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 Bovee 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.

Keywords

alcoholic fermentation, Artificial Neural Networks, modelling

Documents