Artificial neural network model for biosorption of methylene blue by dead leaves of Posidonia oceanica (L.) Delile

Title:

Artificial neural network model for biosorption of methylene blue by dead leaves of Posidonia oceanica (L.) Delile

Creator:

Demir, Guleser K., Dural, Ulas Mehmet, Alyuruk , Hakan, and Cavas, Levent

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:edf7f222-5108-413d-b8fe-39444a30fdca
uuid:edf7f222-5108-413d-b8fe-39444a30fdca
doi:10.14311/NNW.2012.22.029

Subject:

Biosorption, modeling, artificial neural network, and Posidonia oceanica

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In the present study, an alternative promising evaluation method was recommended for dead leaves of Posidonia oceanica (L.) Delile as an adsorbent for biosorption of Methylene Blue (MB). The data from batch experiments were modeled by using Artificial Neural Network (ANN). The optimal operation conditions for biosorption of MB by P. oceanica dead leaves were found for pH, adsorbent dosage, temperature and initial dye concentration as 6, 0.3 g, 303 K and 50 mg/L, respectively. The adsorption reached equilibrium after 30 minutes. According to the results of sensitivity analysis, relative importance of temperature, dye concentration, pH, adsorbent dosage and process time on the biosorption of MB were 33%, 27%, 21%, 10% and 8%, respectively. Minimum mean square error (MSE) was found as 0.0169 by ANN modeling. The present study reveals a novel strategy for adsorption studies to utilize the highly accumulated biomass of dead leaves of P. oceanica in Turkish coastlines instead of burning these dead leaves.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2012 Volume:22 | Number:5

Harvested from:

CDK

Metadata only:

false