Applications of recurrent neural networks in batch reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid

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dc.contributor.author Galván León, Inés María
dc.contributor.author Zaldívar, J.M.
dc.date.accessioned 2009-06-04T12:25:59Z
dc.date.available 2009-06-04T12:25:59Z
dc.date.issued 1997-12
dc.identifier.bibliographicCitation Chemical engineering and processing, vol. 36, n. 6 (1997), p. 505-518
dc.identifier.issn 0255-2701
dc.identifier.uri http://hdl.handle.net/10016/4350
dc.description.abstract This paper is focused on the development of nonlinear models, using artificial neural networks, able to provide appropriate predictions when acting as process simulators. The dynamic behaviour of the heat transfer fluid temperature in a jacketed chemical reactor has been selected as a case study. Different structures of NARMA (Non-linear ARMA) models have been studied. The experimental results have allowed to carry out a comparison between the different neural approaches and a first-principles model. The best neural results are obtained using a parallel model structure based on a recurrent neural network architecture, which guarantees better dynamic approximations than currently employed neural models. The results suggest that parallel models built up with recurrent networks can be seen as an alternative to phenomenological models for simulating the dynamic behaviour of the heating/cooling circuits which change from batch installation to installation.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other Neural networks
dc.subject.other Batch reactors
dc.subject.other Mathematical modelling
dc.subject.other Systems identification
dc.title Applications of recurrent neural networks in batch reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/S0255-2701(97)00030-5
dc.subject.eciencia Informática
dc.identifier.doi 10.1016/S0255-2701(97)00030-5
dc.rights.accessRights openAccess
dc.identifier.publicationfirstpage 505
dc.identifier.publicationissue 6
dc.identifier.publicationlastpage 518
dc.identifier.publicationtitle Chemical engineering and processing
dc.identifier.publicationvolume 36
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