Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Gomes, Adriano de Araújo lattes
Orientador(a): Araújo, Mário César Ugulino de lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal da Paraíba
Programa de Pós-Graduação: Programa de Pós-Graduação em Química
Departamento: Química
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.ufpb.br/jspui/handle/tede/8196
Resumo: In this work it was developed a new strategy for intervals selection using the successive projections algorithm (SPA) coupled to N-PLS and U-PLS models, both with residual bilinearização (RBL) as a post-calibration step. The new algorithm coupled to N-PLS/RBL models was evaluated in two cases of studies. The first was simulated data for quantitation of two analytes (A and B) in the presence of a single interfering. On the second study was conducted a quantitation of ofloxacin in water in the presence of interferents (ciprofloxacin and danofloxacin) by means of liquid chromatography with diode array detection (LC-DAD) data modeling. The results were compared to the N-PLS/RBL model and the variables selection with the genetic algorithm (GA-N-PLS/RBL). In the first case of study (simulated data) were observed RMSEP values (x 10-3 in arbitrary units) for the analytes A and B in the order of 6.7 to 47.6; 10.6 to 11.4; and 6.0 to 14.0 for the N-PLS/RBL, Ga-N-PLS/RBL and the proposed method, respectively. On the second case of study (HPLC-DAD data) RMSEP value (mg/L) of 0.72 (N-PLS/RBL); 0.70 (GA-N-PLS/RBL) and 0.64 (iSPA N-PLS/RBL) were obtained. When combined with the U-PLS/RBL, the new algorithm was evaluated in the EEM modeling in the presence of inner filter effect. Simulated data and quantitation of phenylephrine in the presence of acetaminophen in water sample and interferences (ibuprofen and acetylsalicylic acid) were used as a case of studies. The results were compared to the U-PLS/RBL and e twell established method PARAFAC. For simulated data was observed the following RMSEP values (in arbitrary units) 1.584; 0.077 and 0.066 for PARAFAC; U-PLS/RBL and the proposed method, respectively. In the quantitation of phenylephrine the found RMSEP (in μg/L) were of 0.164 (PARAFAC); 0.089 (U-PLS/RBL) and 0.069 (ISPA-U-PLS/RBL). In all cases it was shown that variables selection is a useful tool capable of improving accuracy when compared with the respective global models (model without variables selection) leading to more parsimonious models. It was observed in all cases, that the sensitivity loss promoted by variables selection is compensated by using more selective channels, justifying the obtained RMSEP smaller values. Finally, it was also observed that the models based on variables selection such as the proposed method were free from significant bias at 95% confidence.
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spelling 2016-05-12T12:35:36Z2018-07-21T00:29:42Z2018-07-21T00:29:42Z2015-06-29GOMES, Adriano de Araujo. Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem, 2015. 126 f. Tese (Doutorado em Química) - Universidade Federal da Paraíba, João Pessoa, 2015.https://repositorio.ufpb.br/jspui/handle/tede/8196In this work it was developed a new strategy for intervals selection using the successive projections algorithm (SPA) coupled to N-PLS and U-PLS models, both with residual bilinearização (RBL) as a post-calibration step. The new algorithm coupled to N-PLS/RBL models was evaluated in two cases of studies. The first was simulated data for quantitation of two analytes (A and B) in the presence of a single interfering. On the second study was conducted a quantitation of ofloxacin in water in the presence of interferents (ciprofloxacin and danofloxacin) by means of liquid chromatography with diode array detection (LC-DAD) data modeling. The results were compared to the N-PLS/RBL model and the variables selection with the genetic algorithm (GA-N-PLS/RBL). In the first case of study (simulated data) were observed RMSEP values (x 10-3 in arbitrary units) for the analytes A and B in the order of 6.7 to 47.6; 10.6 to 11.4; and 6.0 to 14.0 for the N-PLS/RBL, Ga-N-PLS/RBL and the proposed method, respectively. On the second case of study (HPLC-DAD data) RMSEP value (mg/L) of 0.72 (N-PLS/RBL); 0.70 (GA-N-PLS/RBL) and 0.64 (iSPA N-PLS/RBL) were obtained. When combined with the U-PLS/RBL, the new algorithm was evaluated in the EEM modeling in the presence of inner filter effect. Simulated data and quantitation of phenylephrine in the presence of acetaminophen in water sample and interferences (ibuprofen and acetylsalicylic acid) were used as a case of studies. The results were compared to the U-PLS/RBL and e twell established method PARAFAC. For simulated data was observed the following RMSEP values (in arbitrary units) 1.584; 0.077 and 0.066 for PARAFAC; U-PLS/RBL and the proposed method, respectively. In the quantitation of phenylephrine the found RMSEP (in μg/L) were of 0.164 (PARAFAC); 0.089 (U-PLS/RBL) and 0.069 (ISPA-U-PLS/RBL). In all cases it was shown that variables selection is a useful tool capable of improving accuracy when compared with the respective global models (model without variables selection) leading to more parsimonious models. It was observed in all cases, that the sensitivity loss promoted by variables selection is compensated by using more selective channels, justifying the obtained RMSEP smaller values. Finally, it was also observed that the models based on variables selection such as the proposed method were free from significant bias at 95% confidence.Neste trabalho foi desenvolvida uma nova estratégia para seleção de intervalos empregando o algoritmo das projeções sucessivas (SPA) acoplado a modelos N-PLS e U-PLS, ambos com etapa pós-calibração de bilinearização residual (RBL). O novo algoritmo acoplado a modelos N-PLS/RBL, foi avaliado em dois estudos de casos. O primeiro envolvendo dados simulados para quantificação de dois analitos (A e B) na presença de um único interferente. No segundo foi conduzida a quantificação de ofloxacina em água na presença de interferentes (ciprofloxacina e danofloxacina) por meio da modelagem de dados cromatografia liquida com detecção por arranjo de diodos (LC-DAD). Os resultados obtidos foram comparados ao modelo N-PLS/RBL e a seleção de variáveis com o algoritmo genético (GA-N-PLS/RBL). No primeiro estudo de caso (dados simulados) foram observados valores de RMSEP (x 10-3 em unidades arbitrárias) para os analitos A e B da ordem de 6,7 e 47,6; 10,6 e 11,4; 6,0 e 14,0 para o N-PLS/RBL, GA-N-PLS/RBL e o método proposto, respectivamente. No segundo estudo de caso (dados HPLC-DAD) valores de RMSEP (em mg/L) de 0,72 (N-PLS/RBL); 0,70 (GA-N-PLS/RBL) e 0,64 (iSPA-N-PLS/RBL) foram obtidos. Quando combinado com o U-PLS/RBL o novo algoritmo foi avaliado na modelagem de EEM em presença efeito de filtro interno. Dados simulados e a quantificação de fenilefrina na presença de paracetamol em amostras de água e interferentes (Ibuprofeno e ácido acetil salicílico) foram usados como estudos de caso. Os resultados obtidos foram comparados ao modelo U-PLS/RBL e ao bem estabelecido método PARAFAC. Para dados simulados foram observado os seguintes valores de RMSEP (em unidades arbitrarias) 1,584; 0,077 e 0,066 para o PARAFAC; U-PLS/RBL e método proposto, respectivamente. Na quantificação de fenilefrina os RMSEP (em μg/L) encontrados foram de 0,164 (PARAFAC); 0,089 (U-PLS/RBL) e 0,069 (iSPA-U-PLS/RBL). Em todos os casos foi demostrado que seleção de variáveis é uma ferramenta útil capaz de melhorar a acurácia quando comparados aos respectivos modelos globais (modelo sem seleção de variáveis) e tornar os modelos mais parcimoniosos. Foi observado ainda para todos os casos, que a perda de sensibilidade promovida pela seleção de variáveis é compensada pelo uso de canais mais seletivos, justificando os menores valores de RMSEP obtidos. E por fim, foi também observado que os modelos baseados em seleção de variáveis como o método proposto foram isentos de bias significativos a 95% de confiança.Submitted by Maike Costa (maiksebas@gmail.com) on 2016-05-12T12:35:36Z No. of bitstreams: 1 arquivo total.pdf: 5933598 bytes, checksum: f90080e0529915a4c5c37308259bee89 (MD5)Made available in DSpace on 2016-05-12T12:35:36Z (GMT). No. of bitstreams: 1 arquivo total.pdf: 5933598 bytes, checksum: f90080e0529915a4c5c37308259bee89 (MD5) Previous issue date: 2015-06-29Made available in DSpace on 2018-07-21T00:29:42Z (GMT). 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dc.title.por.fl_str_mv Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
title Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
spellingShingle Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
Gomes, Adriano de Araújo
Seleção de intervalos
Dados multivias
Efeito de filtro interno
Vantagem de segunda ordem
Multiway data
Inner filter effect
Second order advantage
Intervals selection
CIENCIAS EXATAS E DA TERRA::QUIMICA
title_short Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
title_full Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
title_fullStr Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
title_full_unstemmed Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
title_sort Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem
author Gomes, Adriano de Araújo
author_facet Gomes, Adriano de Araújo
author_role author
dc.contributor.advisor1.fl_str_mv Araújo, Mário César Ugulino de
dc.contributor.advisor1ID.fl_str_mv 16075056491
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/7281739070942782
dc.contributor.authorID.fl_str_mv 07895419471
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/2719243260954101
dc.contributor.author.fl_str_mv Gomes, Adriano de Araújo
contributor_str_mv Araújo, Mário César Ugulino de
dc.subject.por.fl_str_mv Seleção de intervalos
Dados multivias
Efeito de filtro interno
Vantagem de segunda ordem
Multiway data
Inner filter effect
Second order advantage
topic Seleção de intervalos
Dados multivias
Efeito de filtro interno
Vantagem de segunda ordem
Multiway data
Inner filter effect
Second order advantage
Intervals selection
CIENCIAS EXATAS E DA TERRA::QUIMICA
dc.subject.eng.fl_str_mv Intervals selection
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA::QUIMICA
description In this work it was developed a new strategy for intervals selection using the successive projections algorithm (SPA) coupled to N-PLS and U-PLS models, both with residual bilinearização (RBL) as a post-calibration step. The new algorithm coupled to N-PLS/RBL models was evaluated in two cases of studies. The first was simulated data for quantitation of two analytes (A and B) in the presence of a single interfering. On the second study was conducted a quantitation of ofloxacin in water in the presence of interferents (ciprofloxacin and danofloxacin) by means of liquid chromatography with diode array detection (LC-DAD) data modeling. The results were compared to the N-PLS/RBL model and the variables selection with the genetic algorithm (GA-N-PLS/RBL). In the first case of study (simulated data) were observed RMSEP values (x 10-3 in arbitrary units) for the analytes A and B in the order of 6.7 to 47.6; 10.6 to 11.4; and 6.0 to 14.0 for the N-PLS/RBL, Ga-N-PLS/RBL and the proposed method, respectively. On the second case of study (HPLC-DAD data) RMSEP value (mg/L) of 0.72 (N-PLS/RBL); 0.70 (GA-N-PLS/RBL) and 0.64 (iSPA N-PLS/RBL) were obtained. When combined with the U-PLS/RBL, the new algorithm was evaluated in the EEM modeling in the presence of inner filter effect. Simulated data and quantitation of phenylephrine in the presence of acetaminophen in water sample and interferences (ibuprofen and acetylsalicylic acid) were used as a case of studies. The results were compared to the U-PLS/RBL and e twell established method PARAFAC. For simulated data was observed the following RMSEP values (in arbitrary units) 1.584; 0.077 and 0.066 for PARAFAC; U-PLS/RBL and the proposed method, respectively. In the quantitation of phenylephrine the found RMSEP (in μg/L) were of 0.164 (PARAFAC); 0.089 (U-PLS/RBL) and 0.069 (ISPA-U-PLS/RBL). In all cases it was shown that variables selection is a useful tool capable of improving accuracy when compared with the respective global models (model without variables selection) leading to more parsimonious models. It was observed in all cases, that the sensitivity loss promoted by variables selection is compensated by using more selective channels, justifying the obtained RMSEP smaller values. Finally, it was also observed that the models based on variables selection such as the proposed method were free from significant bias at 95% confidence.
publishDate 2015
dc.date.issued.fl_str_mv 2015-06-29
dc.date.accessioned.fl_str_mv 2016-05-12T12:35:36Z
2018-07-21T00:29:42Z
dc.date.available.fl_str_mv 2018-07-21T00:29:42Z
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dc.identifier.citation.fl_str_mv GOMES, Adriano de Araujo. Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem, 2015. 126 f. Tese (Doutorado em Química) - Universidade Federal da Paraíba, João Pessoa, 2015.
dc.identifier.uri.fl_str_mv https://repositorio.ufpb.br/jspui/handle/tede/8196
identifier_str_mv GOMES, Adriano de Araujo. Algoritmo das projeções sucessivas para seleção de variáveis em calibração de segunda ordem, 2015. 126 f. Tese (Doutorado em Química) - Universidade Federal da Paraíba, João Pessoa, 2015.
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dc.publisher.department.fl_str_mv Química
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