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Comparison between artificial neural networks and Hermia's models to assess ultrafiltration performance

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Comparison between artificial neural networks and Hermia's models to assess ultrafiltration performance

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Corbatón Báguena, MJ.; Vincent Vela, MC.; Gozálvez-Zafrilla, JM.; Alvarez Blanco, S.; Lora-García, J.; Catalán Martínez, D. (2016). Comparison between artificial neural networks and Hermia's models to assess ultrafiltration performance. Separation and Purification Technology. 170:434-444. doi:10.1016/j.seppur.2016.07.007

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/81740

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Title: Comparison between artificial neural networks and Hermia's models to assess ultrafiltration performance
Author:
UPV Unit: Universitat Politècnica de València. Instituto de Seguridad Industrial, Radiofísica y Medioambiental - Institut de Seguretat Industrial, Radiofísica i Mediambiental
Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials
Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi
Issued date:
Abstract:
In this work, flux decline during crossflow ultrafiltration of macromolecules with ceramic membranes has been modeled using artificial neural networks. The artificial neural network tested was the multilayer perceptron. ...[+]
Subjects: Artificial neural networks , Crossflow ultrafiltration , Fouling , Modeling
Copyrigths: Reserva de todos los derechos
Source:
Separation and Purification Technology. (issn: 1383-5866 ) (eissn: 1873-3794 )
DOI: 10.1016/j.seppur.2016.07.007
Publisher:
Elsevier
Publisher version: http://doi.org/10.1016/j.seppur.2016.07.007
Thanks:
The Spanish Ministry for Science and Innovation (Project OPTIMEM CTM2010-20248) is kindly acknowledged.
Type: Artículo

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