Hybrid Neural Network Model Of An Industrial Ethanol Fermentation Process Considering The Effect Of Temperature.

dc.creatorMantovanelli, Ivana C C
dc.creatorRivera, Elmer Ccopa
dc.creatorda Costa, Aline C
dc.creatorMaciel Filho, Rubens
dc.date2007-Apr
dc.date2015-11-27T13:10:44Z
dc.date2015-11-27T13:10:44Z
dc.date.accessioned2018-03-29T01:05:57Z
dc.date.available2018-03-29T01:05:57Z
dc.identifierApplied Biochemistry And Biotechnology. v. 137-140, n. 1-12, p. 817-33, 2007-Apr.
dc.identifier1559-0291
dc.identifier10.1007/s12010-007-9100-0
dc.identifierhttp://www.ncbi.nlm.nih.gov/pubmed/18478437
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/197584
dc.identifier18478437
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1297817
dc.descriptionIn this work a procedure for the development of a robust mathematical model for an industrial alcoholic fermentation process was evaluated. The proposed model is a hybrid neural model, which combines mass and energy balance equations with functional link networks to describe the kinetics. These networks have been shown to have a good nonlinear approximation capability, although the estimation of its weights is linear. The proposed model considers the effect of temperature on the kinetics and has the neural network weights reestimated always so that a change in operational conditions occurs. This allow to follow the system behavior when changes in operating conditions occur.
dc.description137-140
dc.description817-33
dc.languageeng
dc.relationApplied Biochemistry And Biotechnology
dc.relationAppl. Biochem. Biotechnol.
dc.rightsfechado
dc.rights
dc.sourcePubMed
dc.subjectComputer Simulation
dc.subjectEthanol
dc.subjectFermentation
dc.subjectGlucose
dc.subjectModels, Biological
dc.subjectNeural Networks (computer)
dc.subjectSaccharomyces Cerevisiae
dc.subjectTemperature
dc.titleHybrid Neural Network Model Of An Industrial Ethanol Fermentation Process Considering The Effect Of Temperature.
dc.typeArtículos de revistas


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