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Identificación Inteligente de un Proceso Fermentativo Usando el Algoritmo GMDH Modificado

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Identificación Inteligente de un Proceso Fermentativo Usando el Algoritmo GMDH Modificado

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dc.contributor.author Hernández, F. es_ES
dc.contributor.author Herrera, F. es_ES
dc.date.accessioned 2020-05-25T18:45:38Z
dc.date.available 2020-05-25T18:45:38Z
dc.date.issued 2012-01-09
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/144306
dc.description.abstract [EN] One of the variables of more interest in the biotechnological processes is the biomass concentration. The continuous, on-line and exact determination of this parameter it is very difficult and expensive. In this work a neural network was used to estimate the biomass concentration in a Feed-batch fermentation process. In the design, the Group Method of Data Handling algorithm, GMDH, is applied with a new structure based on the employment of genetic algorithm and incorporating a feedback loop. The neural equations are restricted to order 2. The pattern was proved in the fermentation of the Pichia pastoris yeast for the production of a vaccine for recombinant methods. The stability and generalization capacity is demonstrated. The proposed method was compared with other neuronal networks attending to behavior of the Mean Square Error. (mse). es_ES
dc.description.abstract [ES] En este trabajo se aborda, de manera particular, un método para el diseño del algoritmo conocido como Group Method of Data Handling, GMDH, típico con lazo recurrente. Una modificación en una de sus fases de entrenamiento permite ampliar el número de variables utilizadas en cada capa y con ello el área de regresión. Consecuentemente se puede obtener una estructura optimizada en sí misma de mayor complejidad, posibilitando la aparición de lazos recurrentes en las capas intermedias. Lo anterior permite una reducción del error en la modelación de procesos no lineales de lento comportamiento, como el crecimiento celular en biorreactores. El modelo se probó en una fermentación tipo feed-batch de la levadura Pichia pastoris. La estabilidad y capacidad de generalización es demostrada. El método propuesto es comparado con el GMDH típico recurrente y con otras estructuras de redes neuronales clásicas. es_ES
dc.language Español es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Neural networks es_ES
dc.subject Recurrent es_ES
dc.subject Genetic Algorithms es_ES
dc.subject Modeling es_ES
dc.subject Fermentation es_ES
dc.subject Redes neuronales es_ES
dc.subject Recurrente es_ES
dc.subject Algoritmo genético es_ES
dc.subject Modelación es_ES
dc.subject Fermentación es_ES
dc.title Identificación Inteligente de un Proceso Fermentativo Usando el Algoritmo GMDH Modificado es_ES
dc.title.alternative Intelligent identification of a fermentative process using modified GMDH Algorithm es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.riai.2011.11.001
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Hernández, F.; Herrera, F. (2012). Identificación Inteligente de un Proceso Fermentativo Usando el Algoritmo GMDH Modificado. Revista Iberoamericana de Automática e Informática industrial. 9(1):3-13. https://doi.org/10.1016/j.riai.2011.11.001 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.riai.2011.11.001 es_ES
dc.description.upvformatpinicio 3 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 9 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\9622 es_ES
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