Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/101553
Type: Artigo de evento
Title: Hybrid Neural Modeling Of Bioprocesses Using Functional Link Networks
Author: Harada L.H.P.
Da Costa A.C.
Maciel Filho R.
Abstract: The objective of this work was to develop a model for an extractive ethanol fermentation in a simple and rapid way. This model must be sufficiently reliable to be used for posterior optimization and control studies. A hybrid neural model was developed, combining mass and energy balances with neural networks, which describe the process kinetics. To determine the best model, two structures of neural networks were compared: the functional link networks and the feedforward neural networks. The two structures are shown to describe well the process kinetics, and the advantages of using the functional link networks are discussed.
Editor: 
Rights: fechado
Identifier DOI: 10.1385/ABAB:98-100:1-9:1009
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-11244292201&partnerID=40&md5=e0b266a291b2f4046ec746e564863122
Date Issue: 2002
Appears in Collections:Unicamp - Artigos e Outros Documentos

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