About: Partial least squares and artificial neural networks for multicomponent analysis from derivative UV-Vis spectra

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This contribution presents a comparative study of the use of PLS and ANNs to analyze A and C mixtures using UV-Vis derivative spectra. The optimum ANN architecture enabling to model the system was established by means of TRAJAN 6.0 program. Several algorithms (Back propagation, Conjugate gradients, Quick propagation, and Delta-Bar Delta algorithm) were used for the training of the ANN to obtain a reliable model. With help of a suitable experimental design in combination with soft ANN modelling, the concentration of both A and C in mixtures can be quantified with an excellent accuracy (about 1 %). The quality of the testing set was evaluated on the basis of the average root mean square error for prediction (RMSEP) calculated from true and found values of A and C concentrations (RMSEP = 0.07 for A and 0.09 for C). It was found that ANN gives better results for the first and second derivative spectra than for original spectra. Furthermore, in comparison with PLS the ANN provides a more reliable and prec This contribution presents a comparative study of the use of PLS and ANNs to analyze A and C mixtures using UV-Vis derivative spectra. The optimum ANN architecture enabling to model the system was established by means of TRAJAN 6.0 program. Several algorithms (Back propagation, Conjugate gradients, Quick propagation, and Delta-Bar Delta algorithm) were used for the training of the ANN to obtain a reliable model. With help of a suitable experimental design in combination with soft ANN modelling, the concentration of both A and C in mixtures can be quantified with an excellent accuracy (about 1 %). The quality of the testing set was evaluated on the basis of the average root mean square error for prediction (RMSEP) calculated from true and found values of A and C concentrations (RMSEP = 0.07 for A and 0.09 for C). It was found that ANN gives better results for the first and second derivative spectra than for original spectra. Furthermore, in comparison with PLS the ANN provides a more reliable and prec (en)
Title	Partial least squares and artificial neural networks for multicomponent analysis from derivative UV-Vis spectra Partial least squares and artificial neural networks for multicomponent analysis from derivative UV-Vis spectra (en)
skos:prefLabel	Partial least squares and artificial neural networks for multicomponent analysis from derivative UV-Vis spectra Partial least squares and artificial neural networks for multicomponent analysis from derivative UV-Vis spectra (en)
skos:notation	RIV/00216224:14310/02:00006479!RIV/2003/AV0/143103/N
http://linked.open.../vavai/riv/strany	P21
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(IAA1163201), Z(MSM 143100011)
http://linked.open...vai/riv/dodaniDat	2003
http://linked.open...aciTvurceVysledku	Havel, Josef Topinková, Jana Trnková, Libuše
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Přírodovědecká fakulta
http://linked.open...dnocenehoVysledku	657830
http://linked.open...ai/riv/idVysledku	RIV/00216224:14310/02:00006479
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Partial least squares (PLS);artificial neural networks(ANN);multicomponent analysis;derivative UV-Vis spectra;adenine;cytosine (en)
http://linked.open.../riv/klicoveSlovo	multicomponent analysis adenine cytosine Partial least squares (PLS) artificial neural networks(ANN) derivative UV-Vis spectra
http://linked.open...ontrolniKodProRIV	[409D60E39F3F]
http://linked.open...v/mistoKonaniAkce	September, 1. -5.2002, Brno Czech Republic
http://linked.open...i/riv/mistoVydani	Czech Republic, Brno
http://linked.open...i/riv/nazevZdroje	International Chemometric Conference - CHEMOMETRICS VI
http://linked.open...in/vavai/riv/obor	CB
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...ocetUcastnikuAkce	0 (xsd:int)
http://linked.open...nichUcastnikuAkce	0 (xsd:int)
http://linked.open...vavai/riv/projekt	Application of adsorptive transfer and elemination techniques in oligonucleotides and nucleic acids analysis.
http://linked.open...UplatneniVysledku	2002
http://linked.open...iv/tvurceVysledku	Havel, Josef Trnková, Libuše Peňa-Méndez, Eladia M. Topinková, Jana
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2002-01-01 (xsd:date)
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20143100011
number of pages	1 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Masaryk University, Brno, Czech Republic
https://schema.org/isbn	80-210-2918-8
http://localhost/t...ganizacniJednotka	14310

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