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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/31217
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T09:52:20Zoai: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:34982025-09-03 09:52:21.064CONICET 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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1842269152699482112 |
score |
13.13397 |