Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions.

Patnaik, P R (2005) Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions. Biotechnology letters, 27 (6). pp. 409-15. ISSN 0141-5492

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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.

Item Type:	Article
Additional Information:	Copyright of this article belongs to Springer science.
Subjects:	Q Science > QR Microbiology
Depositing User:	Dr. K.P.S.Sengar
Date Deposited:	08 Jan 2012 05:41
Last Modified:	08 Jan 2012 05:41
URI:	http://crdd.osdd.net/open/id/eprint/178

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