Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/195745
Type: Artigo de periódico
Title: Simulation Of Aerated Lagoon Using Artificial Neural Networks And Multivariate Regression Techniques.
Author: Oliveira-Esquerre, Karla Patricia
da Costa, Aline C
Bruns, Roy Edward
Mori, Milton
Abstract: The 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.
Subject: Biotechnology
Brazil
Models, Theoretical
Multivariate Analysis
Neural Networks (computer)
Oxygen
Paper
Rights: fechado
Identifier DOI: 
Address: http://www.ncbi.nlm.nih.gov/pubmed/12721466
Date Issue: 2003
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

Files in This Item:
File SizeFormat 
pmed_12721466.pdf107.47 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.