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Further enhancement of fed-batch streptokinase yield in the presence of inflow noise by coupled neural networks

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title Further enhancement of fed-batch streptokinase yield in the presence of inflow noise by coupled neural networks
 
Creator Patnaik, P R
 
Subject QD Chemistry
 
Description Noise carried by the feed stream is a common feature of large-scale bioreactor operations. This noise may be modelled by a set of time-dependent Gaussian distributions. Recent studies have shown that neither unfiltered nor completely filtered noise is desirable. The best performance requires optimally filtered noise. A previous publication in this journal showed that streptokinase (SK) activity in a fed-batch fermentation can be improved substantially through controlled static filtering. Later work with β-galactosidase showed that dynamic filtering by means of a neuralnetwork was superior, especially when it was coupled to a neural filter. That concept has been applied to SK. Coupling of two neuralnetworks increased the peak SK activity (in g/l) by 42% over that for a noise-free feed whereas the improvement with a static filter was 22%
 
Publisher Elsevier Science
 
Date 2001
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://crdd.osdd.net/open/869/1/patnaik2001.4.pdf
Patnaik, P R (2001) Further enhancement of fed-batch streptokinase yield in the presence of inflow noise by coupled neural networks. Process Biochemistry, 37 (2). pp. 145-151. ISSN 13595113
 
Relation http://dx.doi.org/10.1016/S0032-9592(01)00190-X
http://crdd.osdd.net/open/869/