12541442

Source:http://linkedlifedata.com/resource/pubmed/id/12541442

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0008550, umls-concept:C0013682, umls-concept:C0598941, umls-concept:C0681842, umls-concept:C1185738, umls-concept:C2004457
pubmed:issue	1
pubmed:dateCreated	2003-1-24
pubmed:abstractText	This paper used artificial neural network (ANN) modeling method to study the relationship between the column efficiency and the operating conditions. This method solved the problem that it is not easy to establish a quantitative model between the column efficiency and its main effecting factors using those traditional modeling methods, as the relationship is usually quite complex and non-linear in fact. The varied-pace BP (back-propagation) learning algorithm was adopted, and a three-layer weight-connected ANN model for a typical dual column system was established. The effective plate number representing the column efficiency acted as the output vectors, while the temperature of the pre-column, the temperature of the main column, the pressure difference between the columns and the vent rate acted as the input vectors. Then the model acquired was used to predict column efficiency (characterized by "effective plate number") under different operating conditions. The results showed that the model predicting value was in consistent with the value found. This work proved that ANN modeling method was suitable for the study on the relationship between the column efficiency of two-dimensional column chromatography system and the operating conditions.
pubmed:language	chi
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/9424804
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Jan
pubmed:issn	1000-8713
pubmed:author	pubmed-author:GuoZ SZS, pubmed-author:HuangJJ, pubmed-author:XuG WGW, pubmed-author:ZengQ XQX
pubmed:issnType	Print
pubmed:volume	18
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	1-4
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:12541442-Algorithms, pubmed-meshheading:12541442-Chromatography, pubmed-meshheading:12541442-Forecasting, pubmed-meshheading:12541442-Neural Networks (Computer)
pubmed:year	2000
pubmed:articleTitle	[Column efficiency prediction of two dimensional chromatography by artificial neural network].
pubmed:affiliation	College of Chemical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
pubmed:publicationType	Journal Article, English Abstract