Hybrid modelling of biotechnological processes using neural networks

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Hybrid modelling of biotechnological processes using neural networks. / Chen, L B; Bernard, O; Bastain, G et al.
In: Control Engineering Practice, Vol. 8, No. 7, 07.2000, p. 821-827.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Chen, LB, Bernard, O, Bastain, G & Angelov, P 2000, 'Hybrid modelling of biotechnological processes using neural networks', Control Engineering Practice, vol. 8, no. 7, pp. 821-827. https://doi.org/10.1016/S0967-0661(00)00036-8

APA

Chen, L. B., Bernard, O., Bastain, G., & Angelov, P. (2000). Hybrid modelling of biotechnological processes using neural networks. Control Engineering Practice, 8(7), 821-827. https://doi.org/10.1016/S0967-0661(00)00036-8

Vancouver

Chen LB, Bernard O, Bastain G, Angelov P. Hybrid modelling of biotechnological processes using neural networks. Control Engineering Practice. 2000 Jul;8(7):821-827. doi: 10.1016/S0967-0661(00)00036-8

Author

Chen, L B ; Bernard, O ; Bastain, G et al. / Hybrid modelling of biotechnological processes using neural networks. In: Control Engineering Practice. 2000 ; Vol. 8, No. 7. pp. 821-827.

Bibtex

@article{9b350cc91ba044509081b598c3f7b898,

title = "Hybrid modelling of biotechnological processes using neural networks",

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",

keywords = "Biotechnology, Identification, Modelling, Neural networks, DCS-publications-id, art-557, DCS-publications-personnel-id, 82",

author = "Chen, {L B} and O Bernard and G Bastain and Plamen Angelov",

note = "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, {\textcopyright} ELSEVIER.",

year = "2000",

month = jul,

doi = "10.1016/S0967-0661(00)00036-8",

language = "English",

volume = "8",

pages = "821--827",

journal = "Control Engineering Practice",

issn = "0967-0661",

publisher = "Elsevier Limited",

number = "7",

}

RIS

TY - JOUR

T1 - Hybrid modelling of biotechnological processes using neural networks

AU - Chen, L B

AU - Bernard, O

AU - Bastain, G

AU - Angelov, Plamen

N1 - 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.

PY - 2000/7

Y1 - 2000/7

N2 - 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

AB - 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

KW - Biotechnology

KW - Identification

KW - Modelling

KW - Neural networks

KW - DCS-publications-id

KW - art-557

KW - DCS-publications-personnel-id

KW - 82

U2 - 10.1016/S0967-0661(00)00036-8

DO - 10.1016/S0967-0661(00)00036-8

M3 - Journal article

VL - 8

SP - 821

EP - 827

JO - Control Engineering Practice

JF - Control Engineering Practice

SN - 0967-0661

IS - 7

ER -

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