The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization

Autores
Araújo Gomes, Adriano de; Alcaraz, Mirta Raquel; Goicoechea, Hector Casimiro; Araújo, Mario Cesar U.
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV–vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL.
Fil: Araújo Gomes, Adriano de. Universidade Federal da Paraíba; Brasil
Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Goicoechea, Hector Casimiro. Universidade Federal da Paraíba; Brasil. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Araújo, Mario Cesar U.. Universidade Federal da Paraíba; Brasil
Materia
Multiway Data
Variable Selection
Second Order Advantage
Second Order Calibration
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/31217
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/31217
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearizationAraújo Gomes, Adriano deAlcaraz, Mirta RaquelGoicoechea, Hector CasimiroAraújo, Mario Cesar U.Multiway DataVariable SelectionSecond Order AdvantageSecond Order Calibrationhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV–vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL.Fil: Araújo Gomes, Adriano de. Universidade Federal da Paraíba; BrasilFil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Goicoechea, Hector Casimiro. Universidade Federal da Paraíba; Brasil. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Araújo, Mario Cesar U.. Universidade Federal da Paraíba; BrasilElsevier2013-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/31217Araújo, Mario Cesar U.; Goicoechea, Hector Casimiro; Alcaraz, Mirta Raquel; Araújo Gomes, Adriano de; The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization; Elsevier; Analytica Chimica Acta; 811; 12-2013; 13-220003-2670CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0003267013015717info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2013.12.022info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:49:57Zoai:ri.conicet.gov.ar:11336/31217instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:49:57.499CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
title The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
spellingShingle The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
Araújo Gomes, Adriano de
Multiway Data
Variable Selection
Second Order Advantage
Second Order Calibration
title_short The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
title_full The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
title_fullStr The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
title_full_unstemmed The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
title_sort The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization
dc.creator.none.fl_str_mv Araújo Gomes, Adriano de
Alcaraz, Mirta Raquel
Goicoechea, Hector Casimiro
Araújo, Mario Cesar U.
author Araújo Gomes, Adriano de
author_facet Araújo Gomes, Adriano de
Alcaraz, Mirta Raquel
Goicoechea, Hector Casimiro
Araújo, Mario Cesar U.
author_role author
author2 Alcaraz, Mirta Raquel
Goicoechea, Hector Casimiro
Araújo, Mario Cesar U.
author2_role author
author
author
dc.subject.none.fl_str_mv Multiway Data
Variable Selection
Second Order Advantage
Second Order Calibration
topic Multiway Data
Variable Selection
Second Order Advantage
Second Order Calibration
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV–vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL.
Fil: Araújo Gomes, Adriano de. Universidade Federal da Paraíba; Brasil
Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Goicoechea, Hector Casimiro. Universidade Federal da Paraíba; Brasil. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Araújo, Mario Cesar U.. Universidade Federal da Paraíba; Brasil
description In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV–vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL.
publishDate 2013
dc.date.none.fl_str_mv 2013-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/31217
Araújo, Mario Cesar U.; Goicoechea, Hector Casimiro; Alcaraz, Mirta Raquel; Araújo Gomes, Adriano de; The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization; Elsevier; Analytica Chimica Acta; 811; 12-2013; 13-22
0003-2670
CONICET Digital
CONICET
url http://hdl.handle.net/11336/31217
identifier_str_mv Araújo, Mario Cesar U.; Goicoechea, Hector Casimiro; Alcaraz, Mirta Raquel; Araújo Gomes, Adriano de; The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization; Elsevier; Analytica Chimica Acta; 811; 12-2013; 13-22
0003-2670
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0003267013015717
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2013.12.022
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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