Neural network modeling of Pb2+ removal from wastewater using electrodialysis

被引：78
|
作者：
Sadrzadeh, Mohtada [1 ]
Mohammadi, Toraj [1 ]
Ivakpour, Javad [2 ]
Kasiri, Norollah [2 ]
机构：
[1] IUST, Dept Chem Engn, Res Ctr Membrane Separat Proc, Tehran, Iran
[2] IUST, Dept Chem Engn, Comp Aided Proc Engn Lab, Tehran, Iran
来源：
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION | 2009年 / 48卷 / 08期
关键词：
Electrodialysis; Neural network; Wastewater treatment; Metal ions; CROSS-FLOW MICROFILTRATION; HEAVY-METAL REMOVAL; FLUX DECLINE; NANOFILTRATION MEMBRANES; MILK ULTRAFILTRATION; ION-EXCHANGE; BLACK-BOX; PREDICTION; DESALINATION; BIOSORPTION;
D O I：
10.1016/j.cep.2009.07.001
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Artificial neural network(ANN) was applied to predict separation percent(SP) of lead ions from wastewater using electrodialysis (ED). The aim was to predict SP of Pb2+ as a function of concentration, temperature, flow rate and voltage. Optimum numbers of hidden layers and nodes in each layer were determined. The selected structure (4:6:2:1) was used for prediction of SP of lead ions as well as current efficiency (CE) of ED cell for different inputs in the domain of training data. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：1371 / 1381
页数：11
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