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dc.contributor.CRUESPUNIVERSIDADE DE ESTADUAL DE CAMPINASpt_BR
dc.typeArtigo de periódicopt_BR
dc.titleSimulation Of Aerated Lagoon Using Artificial Neural Networks And Multivariate Regression Techniques.pt_BR
dc.contributor.authorOliveira-Esquerre, Karla Patriciapt_BR
dc.contributor.authorda Costa, Aline Cpt_BR
dc.contributor.authorBruns, Roy Edwardpt_BR
dc.contributor.authorMori, Miltonpt_BR
unicamp.authorKarla Patricia Oliveira-Esquerre, DPQ/FEQ/UNICAMP, PO Box 6066, 13081-970 Campinas, SP, Brazil. karla@feq.unicamp.brpt_BR
unicamp.author.externalAline C da Costa,pt
unicamp.author.externalRoy Edward Bruns,pt
unicamp.author.externalMilton Mori,pt
dc.subjectBiotechnologypt_BR
dc.subjectBrazilpt_BR
dc.subjectModels, Theoreticalpt_BR
dc.subjectMultivariate Analysispt_BR
dc.subjectNeural Networks (computer)pt_BR
dc.subjectOxygenpt_BR
dc.subjectPaperpt_BR
dc.description.abstractThe aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.en
dc.relation.ispartofApplied Biochemistry And Biotechnologypt_BR
dc.relation.ispartofabbreviationAppl. Biochem. Biotechnol.pt_BR
dc.date.issued2003pt_BR
dc.identifier.citationApplied Biochemistry And Biotechnology. v. 105 -108, p. 437-49, 2003.pt_BR
dc.language.isoengpt_BR
dc.description.volume105 -108pt_BR
dc.description.firstpage437-49pt_BR
dc.rightsfechadopt_BR
dc.sourcePubMedpt_BR
dc.identifier.issn0273-2289pt_BR
dc.identifier.urlhttp://www.ncbi.nlm.nih.gov/pubmed/12721466pt_BR
dc.date.available2015-11-27T12:52:49Z-
dc.date.accessioned2015-11-27T12:52:49Z-
dc.description.provenanceMade available in DSpace on 2015-11-27T12:52:49Z (GMT). No. of bitstreams: 1 pmed_12721466.pdf: 110049 bytes, checksum: 77243925956e872f8df87d94ed7ab4ab (MD5) Previous issue date: 2003en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/195745-
dc.identifier.idPubmed12721466pt_BR
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