Linked Life Data

10203774

Source:http://linkedlifedata.com/resource/pubmed/id/10203774

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1999-5-4
pubmed:abstractText
The on-line control of enzyme-production processes is difficult, owing to the uncertainties typical of biological systems and to the lack of suitable on-line sensors for key process variables. For example, intelligent methods to predict the end point of fermentation could be of great economic value. Computer-assisted control based on artificial-neural-network models offers a novel solution in such situations. Well-trained feedforward-backpropagation neural networks can be used as software sensors in enzyme-process control; their performance can be affected by a number of factors.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0167-7799
pubmed:author
pubmed:issnType
Print
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
155-62
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Applying neural networks as software sensors for enzyme engineering.
pubmed:affiliation
Laboratory of Bioprocess Engineering, Helsinki University of Technology, PO Box 6100, FIN-02015 HUT, Finland.
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't