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Hybrid modelling of biotechnological processes using neural networks

Chen, L B and Bernard, O and Bastain, G and Angelov, Plamen (2000) Hybrid modelling of biotechnological processes using neural networks. Control Engineering Practice, 8 (7). pp. 821-827. ISSN 0967-0661

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Abstract

The hybrid modelling approach for bioprocesses combines a neural network representation of the reaction rates with a mass–balance description of the reactor. A procedure for the identification of hybrid models is proposed and illustrated with an experimental case-study. The key feature is a state transformation which allows to identify separately the kinetic models of the reaction rates even if they occur simultaneously in the reactor. (c) Elsevier

Item Type: Article
Journal or Publication Title: Control Engineering Practice
Additional Information: Cited by over 14 other papers. The final, definitive version of this article has been published in the Journal, Control Engineering Practice 8 (7), 2000, © ELSEVIER.
Uncontrolled Keywords: Biotechnology ; Identification ; Modelling ; Neural networks ; DCS-publications-id ; art-557 ; DCS-publications-personnel-id ; 82
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > Lancaster Environment Centre
Faculty of Science and Technology > School of Computing & Communications
ID Code: 910
Deposited By: Dr. Plamen Angelov
Deposited On: 09 Jan 2008 09:26
Refereed?: Yes
Published?: Published
Last Modified: 03 Jun 2014 16:34
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/910

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