Abstract
Neural Networks were developed to identify different phases in the growth cycle of a recombinant strain of Bacillus subtilis. The network performance was enhanced by adding the first and second derivatives of the cultivation sample absorbance. The new architecture was then coupled to a Jordan network with locally recurrent processing elements in order to forecast the stages of the fermentation based on data collected during the first 5 hours.
Original language | English (US) |
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Pages (from-to) | 301-304 |
Number of pages | 4 |
Journal | Biotechnology Techniques |
Volume | 12 |
Issue number | 4 |
DOIs | |
State | Published - 1998 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Biochemistry
- Applied Microbiology and Biotechnology