Artificial neural networks (ANN) approach for modeling of removal of Lanaset Red G on Chara contraria

被引：65

作者：

Celekli, Abuzer ^{[1
]}

Geyik, Faruk ^{[2
]}

机构：

[1] Gaziantep Univ, Fac Art & Sci, Dept Biol, TR-27310 Gaziantep, Turkey

[2] Gaziantep Univ, Fac Engn, Dept Ind Engn, TR-27310 Gaziantep, Turkey

来源：

BIORESOURCE TECHNOLOGY | 2011年 / 102卷 / 10期

关键词：

Adsorption; ANN; Chara contraria; Lanaset Red G; DYE SOLUTION; EQUILIBRIUM; BIOSORPTION; BIOSORBENTS; MACROALGAE; PARAMETERS; ADSORPTION;

D O I：

10.1016/j.biortech.2011.02.052

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

A three-layer artificial neural network (ANN) was constructed to predict the removal efficiency of Lanaset Red (LR) G on Chara contraria based on 2304 experimental sets. The effects of operating variables (particle size, adsorbent dosage, pH regimes, dye concentration, and contact time) were studied to optimize the sorption conditions of this dye. The operating variables were used as the input to the constructed neural network to predict the dye uptake at any time as the output. This adsorbent was characterized by FTIR. Pseudo second-order model was also fitted to the experimental data. According to values of error analyses and determinations coefficient, the ANN was more appropriate to describe this adsorption process. Result of this model indicated that pH regimes had the highest importance effect (49%) on the dye uptake. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：5634 / 5638

页数：5

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