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

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

PDF patnaik2001.4.pdf - Published Version Restricted to Registered users only Download (134Kb) | Request a copy

Abstract

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%

Item Type:	Article
Additional Information:	Copyright of this artiocle belongs to Elsevier Science.
Uncontrolled Keywords:	Streptokinase fermentation; Inflownoise; Neural filtering; Neural control
Subjects:	Q Science > QD Chemistry
Depositing User:	Dr. K.P.S.Sengar
Date Deposited:	03 Feb 2012 16:14
Last Modified:	09 Jan 2015 10:24
URI:	http://crdd.osdd.net/open/id/eprint/869

Actions (login required)

View Item