Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis

Detalhes bibliográficos
Autor(a) principal: Oliveira-Esquerre,K.P.
Data de Publicação: 2002
Outros Autores: Mori,M., Bruns,R.E.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Chemical Engineering
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322002000400002
Resumo: This work presents a way to predict the biochemical oxygen demand (BOD) of the output stream of the biological wastewater treatment plant at RIPASA S/A Celulose e Papel, one of the major pulp and paper plants in Brazil. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a backpropagated neural network. The influence of input variables is analyzed and satisfactory prediction results are obtained for an optimized situation.
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spelling Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysisArtificial neural networksPrincipal components analysisWastewater treatment and Biochemical oxygen demandThis work presents a way to predict the biochemical oxygen demand (BOD) of the output stream of the biological wastewater treatment plant at RIPASA S/A Celulose e Papel, one of the major pulp and paper plants in Brazil. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a backpropagated neural network. The influence of input variables is analyzed and satisfactory prediction results are obtained for an optimized situation.Brazilian Society of Chemical Engineering2002-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322002000400002Brazilian Journal of Chemical Engineering v.19 n.4 2002reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/S0104-66322002000400002info:eu-repo/semantics/openAccessOliveira-Esquerre,K.P.Mori,M.Bruns,R.E.eng2003-01-20T00:00:00Zoai:scielo:S0104-66322002000400002Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2003-01-20T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false
dc.title.none.fl_str_mv Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
title Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
spellingShingle Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
Oliveira-Esquerre,K.P.
Artificial neural networks
Principal components analysis
Wastewater treatment and Biochemical oxygen demand
title_short Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
title_full Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
title_fullStr Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
title_full_unstemmed Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
title_sort Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
author Oliveira-Esquerre,K.P.
author_facet Oliveira-Esquerre,K.P.
Mori,M.
Bruns,R.E.
author_role author
author2 Mori,M.
Bruns,R.E.
author2_role author
author
dc.contributor.author.fl_str_mv Oliveira-Esquerre,K.P.
Mori,M.
Bruns,R.E.
dc.subject.por.fl_str_mv Artificial neural networks
Principal components analysis
Wastewater treatment and Biochemical oxygen demand
topic Artificial neural networks
Principal components analysis
Wastewater treatment and Biochemical oxygen demand
description This work presents a way to predict the biochemical oxygen demand (BOD) of the output stream of the biological wastewater treatment plant at RIPASA S/A Celulose e Papel, one of the major pulp and paper plants in Brazil. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a backpropagated neural network. The influence of input variables is analyzed and satisfactory prediction results are obtained for an optimized situation.
publishDate 2002
dc.date.none.fl_str_mv 2002-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322002000400002
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322002000400002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0104-66322002000400002
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
publisher.none.fl_str_mv Brazilian Society of Chemical Engineering
dc.source.none.fl_str_mv Brazilian Journal of Chemical Engineering v.19 n.4 2002
reponame:Brazilian Journal of Chemical Engineering
instname:Associação Brasileira de Engenharia Química (ABEQ)
instacron:ABEQ
instname_str Associação Brasileira de Engenharia Química (ABEQ)
instacron_str ABEQ
institution ABEQ
reponame_str Brazilian Journal of Chemical Engineering
collection Brazilian Journal of Chemical Engineering
repository.name.fl_str_mv Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)
repository.mail.fl_str_mv rgiudici@usp.br||rgiudici@usp.br
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