ICAR Research Data Repository for Knowledge Management
Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions.
DIR@IMTECH: CSIR-Institute of Microbial Technology
View Archive Info| Field | Value | |
| Title |
Neural network designs for poly-beta-hydroxybutyrate production optimization under simulated industrial conditions.
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| Creator |
Patnaik, P R
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| Subject |
QR Microbiology
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| Description |
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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| Publisher |
Springer Science
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| Date |
2005-03
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://crdd.osdd.net/open/178/1/patnaik2005.pdf
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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| Relation |
http://www.springerlink.com/content/q06u276873843413/
http://crdd.osdd.net/open/178/ |
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