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dc.contributor.authorOtálora Berenguel, Pablo 
dc.contributor.authorGuzmán, José Luis
dc.contributor.authorBerenguel Soria, Manuel 
dc.contributor.authorAcién Fernández, Francisco Gabriel 
dc.date.accessioned2022-04-19T11:34:49Z
dc.date.available2022-04-19T11:34:49Z
dc.date.issued2020-09-19
dc.identifier.urihttp://hdl.handle.net/10835/13624
dc.description.abstractThis paper presents a black-box dynamic model for microalgae production in raceway reactors. The black-box model, developed using Deep Learning techniques, allows the estimation of the pH in a 100 m2 raceway reactor. The model has been created using only and exclusively data, what gives a high ease of use. The results obtained verify the effectiveness of this type of techniques for the modelling of complex dynamic processes. The model was validated for different weather conditions obtaining satisfactory results. Thus, the obtained model is fairly useful for simulation purposes or for the implementation of model-based control techniques.es_ES
dc.language.isoenes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDynamic Model for the pH in a Raceway Reactor using Deep Learning techniqueses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.relation.projectIDhttp://eu-repo/grantAgreement/ES/MINECO/2016SABANA/ES/Sustainable%20Algae%20Biorefinery%20for%20Agriculture%20aNd%20Aquaculture/SABANA/es_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional