%0 Journal Article
%@ 0141-5492
%A Patnaik, P R
%D 2005
%F open:178
%I Springer Science
%J Biotechnology letters
%N 6
%P 409-15
%T Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions.
%U http://crdd.osdd.net/open/178/
%V 27
%X 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.
%Z Copyright of this article belongs to Springer science.