Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions.
Biotechnol Lett
; 27(6): 409-15, 2005 Mar.
Article
en En
| MEDLINE
| ID: mdl-15834806
ABSTRACT
Improvement of the fermentation efficiency of poly-beta-hydroxybutyrate (PHB) may make it competitive with chemically synthesized petroleum-based polymers. One step toward this is optimization of fluid dispersion and the feed rates to a fed-batch bioreactor. In a recent study using a fermentation model, dispersion corresponding to a Peclet number of approximately 20 was shown to maximize the productivity of PHB. Here further improvement has been investigated using neural optimization. A comparison of seven neural topologies has shown that while feed-forward and radial basis neural networks are computationally efficient, recurrent networks generate higher concentrations of PHB. All networks enhanced the productivity by 16-93% over model-based optimization.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Poliésteres
/
Microbiología Industrial
/
Redes Neurales de la Computación
/
Hidroxibutiratos
Idioma:
En
Revista:
Biotechnol Lett
Año:
2005
Tipo del documento:
Article
País de afiliación:
India