Modeling of electrochemical removal of cadmium under galvanostatic mode using an artificial neural network

D. E. Millán-Ocampo, A. Parrales-Bahena, Ma de Lourdes Llovera-Hernández, S. Silva-Martínez, J. Porcayo-Calderón, J. A. Hernández*

*Autor correspondiente de este trabajo

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

3 Citas (Scopus)

Resumen

In this research, the final concentration of cadmium in an electrochemical removal process is estimated by an artificial neural network (ANN) model. The ANN model based on experimental data obtained by a removal process of cadmium from dilute aqueous solutions under galvanostatic mode in a flow-through cell. The pH, current density, and electrolysis time were considered as input variables. An analysis of the hyperbolic tangential-sigmoidal (TANSIG) and logarithmic-sigmoidal (LOGSIG) transfer function was developed to obtain the best accuracy model. To validate the accuracy and the adaptability of the model proposed, statistical and linearity tests (slope-intercept) were performed. The best model with architecture 3:3:1 was validated with a R2 value of 0.9850 and a MSE value of 0.00166, besides approved linearity tests with 99% confidence.

Idioma originalInglés
Páginas (desde-hasta)7437-7446
Número de páginas10
PublicaciónInternational Journal of Environmental Science and Technology
Volumen19
N.º8
DOI
EstadoPublicada - ago 2022

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© 2021, Islamic Azad University (IAU).

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