Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach

Autores
Olivieri, Alejandro Cesar; Magallanes, Jorge Federico
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Screening of relevant factors using Plackett–Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett–Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search.
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
Materia
Plackett–Burman designs
Factor associations
Ant colony optimization
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:11336/105509

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spelling Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approachOlivieri, Alejandro CesarMagallanes, Jorge FedericoPlackett–Burman designsFactor associationsAnt colony optimizationhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Screening of relevant factors using Plackett–Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett–Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search.Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; ArgentinaElsevier Science2012-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/105509Olivieri, Alejandro Cesar; Magallanes, Jorge Federico; Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach; Elsevier Science; Talanta; 97; 8-2012; 242-2480039-9140CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0039914012003207info:eu-repo/semantics/altIdentifier/doi/10.1016/j.talanta.2012.04.025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:44:37Zoai:ri.conicet.gov.ar:11336/105509instacron: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 09:44:37.421CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
title Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
spellingShingle Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
Olivieri, Alejandro Cesar
Plackett–Burman designs
Factor associations
Ant colony optimization
title_short Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
title_full Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
title_fullStr Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
title_full_unstemmed Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
title_sort Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach
dc.creator.none.fl_str_mv Olivieri, Alejandro Cesar
Magallanes, Jorge Federico
author Olivieri, Alejandro Cesar
author_facet Olivieri, Alejandro Cesar
Magallanes, Jorge Federico
author_role author
author2 Magallanes, Jorge Federico
author2_role author
dc.subject.none.fl_str_mv Plackett–Burman designs
Factor associations
Ant colony optimization
topic Plackett–Burman designs
Factor associations
Ant colony optimization
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Screening of relevant factors using Plackett–Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett–Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search.
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
description Screening of relevant factors using Plackett–Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett–Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
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/11336/105509
Olivieri, Alejandro Cesar; Magallanes, Jorge Federico; Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach; Elsevier Science; Talanta; 97; 8-2012; 242-248
0039-9140
CONICET Digital
CONICET
url http://hdl.handle.net/11336/105509
identifier_str_mv Olivieri, Alejandro Cesar; Magallanes, Jorge Federico; Uncovering interactions in Plackett–Burman screening designs applied to analytical systems: A Monte Carlo ant colony optimization approach; Elsevier Science; Talanta; 97; 8-2012; 242-248
0039-9140
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0039914012003207
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.talanta.2012.04.025
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
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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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