Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models

Artificial Neural Network (ANN) and Group Method Data Handling (GMDH) models, a kind of polynomial neural network, were used to predict the breakthrough curves of rhamnolipids onto activated carbon and Amberlite XAD-2 adsorbents. Rhamnolipids were produced by Pseudomonas aeruginosa and were previous...

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Principais autores: Souza, Domingos Fabiano de Santana, Padilha, Carlos Eduardo de Araújo, Padilha, Carlos Alberto de Araújo, Oliveira, Jackson Araújo de, Macedo, Gorete Ribeiro de, Santos, Everaldo Silvino dos
Formato: article
Idioma:English
Publicado em: Elsevier
Assuntos:
Rhamnolipids
Adsorption
Breakthrough curves
ANN model
GMDH model
Acesso em linha:https://repositorio.ufrn.br/handle/123456789/45196
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spelling ri-123456789-451962023-02-14T19:52:19Z Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models Souza, Domingos Fabiano de Santana Padilha, Carlos Eduardo de Araújo Padilha, Carlos Alberto de Araújo Oliveira, Jackson Araújo de Macedo, Gorete Ribeiro de Santos, Everaldo Silvino dos Rhamnolipids Adsorption Breakthrough curves ANN model GMDH model Artificial Neural Network (ANN) and Group Method Data Handling (GMDH) models, a kind of polynomial neural network, were used to predict the breakthrough curves of rhamnolipids onto activated carbon and Amberlite XAD-2 adsorbents. Rhamnolipids were produced by Pseudomonas aeruginosa and were previously purified using acidic precipitation coupled to petroleum ether extraction. Network training was carried out by changing operational conditions such as linear flow velocity, packed bed height as well as the initial rhamnolipid concentration. Predicted data were compared to experimental ones in order to evaluate the two models' (ANN and GDMH) performance. The percentage of absolute average deviation (% AAD) obtained to ANN was 10.10% when the activated carbon data were used and 11.34% for the Amberlite XAD-2 data. When the GMDH model was used the % AAD was 32.54% and 35.98%, for the data of activated carbon and Amberlite XAD-2, respectively. Therefore ANN model showed a better performance to predict the breakthrough curves of rhamnolipids onto the two adsorbents than GMDH 2021-12-06T18:34:26Z 2021-12-06T18:34:26Z 2015-06 article PADILHA, Carlos Eduardo de Araújo; PADILHA, Carlos Alberto de Araújo; SOUZA, Domingos Fabiano de Santana; OLIVEIRA, Jackson Araújo de; MACEDO, Gorete Ribeiro de; SANTOS, Everaldo Silvino dos. Prediction of rhamnolipid breakthrough curves on activated carbon and Amberlite XAD-2 using Artificial Neural Network and Group Method Data Handling models. Journal Of Molecular Liquids, [S.L.], v. 206, p. 293-299, jun. 2015. Elsevier BV. http://dx.doi.org/10.1016/j.molliq.2015.02.030. Disponível em: https://www.sciencedirect.com/science/article/pii/S0167732215001208?via%3Dihub. Acesso em: 05 nov. 2021. 0167-7322 https://repositorio.ufrn.br/handle/123456789/45196 10.1016/j.molliq.2015.02.030 en Elsevier
institution Repositório Institucional
collection RI - UFRN
language English
topic Rhamnolipids
Adsorption
Breakthrough curves
ANN model
GMDH model
spellingShingle Rhamnolipids
Adsorption
Breakthrough curves
ANN model
GMDH model
Souza, Domingos Fabiano de Santana
Padilha, Carlos Eduardo de Araújo
Padilha, Carlos Alberto de Araújo
Oliveira, Jackson Araújo de
Macedo, Gorete Ribeiro de
Santos, Everaldo Silvino dos
Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
description Artificial Neural Network (ANN) and Group Method Data Handling (GMDH) models, a kind of polynomial neural network, were used to predict the breakthrough curves of rhamnolipids onto activated carbon and Amberlite XAD-2 adsorbents. Rhamnolipids were produced by Pseudomonas aeruginosa and were previously purified using acidic precipitation coupled to petroleum ether extraction. Network training was carried out by changing operational conditions such as linear flow velocity, packed bed height as well as the initial rhamnolipid concentration. Predicted data were compared to experimental ones in order to evaluate the two models' (ANN and GDMH) performance. The percentage of absolute average deviation (% AAD) obtained to ANN was 10.10% when the activated carbon data were used and 11.34% for the Amberlite XAD-2 data. When the GMDH model was used the % AAD was 32.54% and 35.98%, for the data of activated carbon and Amberlite XAD-2, respectively. Therefore ANN model showed a better performance to predict the breakthrough curves of rhamnolipids onto the two adsorbents than GMDH
format article
author Souza, Domingos Fabiano de Santana
Padilha, Carlos Eduardo de Araújo
Padilha, Carlos Alberto de Araújo
Oliveira, Jackson Araújo de
Macedo, Gorete Ribeiro de
Santos, Everaldo Silvino dos
author_facet Souza, Domingos Fabiano de Santana
Padilha, Carlos Eduardo de Araújo
Padilha, Carlos Alberto de Araújo
Oliveira, Jackson Araújo de
Macedo, Gorete Ribeiro de
Santos, Everaldo Silvino dos
author_sort Souza, Domingos Fabiano de Santana
title Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
title_short Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
title_full Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
title_fullStr Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
title_full_unstemmed Prediction of rhamnolipid breakthrough curves on activated carbon and amberlite XAD-2 using artificial neural network and group method data handling models
title_sort prediction of rhamnolipid breakthrough curves on activated carbon and amberlite xad-2 using artificial neural network and group method data handling models
publisher Elsevier
publishDate 2021
url https://repositorio.ufrn.br/handle/123456789/45196
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