Modeling and Optintation of Heterogeneous Photo-Fenton Process with Response Surface Methodology and Artificial Neural Networks

In this study, estimation capacities of response surface methodology (RSM) and artificial neural network (ANN) in a heterogeneous photo-Fenton process were investigated. The zeolite Fe-ZSM5 was used as heterogeneous catalyst of the process for degradation of C.I. Acid Red 14 azo dye. The efficiency...

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Bibliographic Details
Published in:Environmental science & technology 2008-11, Vol.42 (21), p.7970
Main Authors: Kasiri, M B, Aleboyeh, H, Aleboyeh, A
Format: Article
Language:English
Subjects:
Dyes
Efficiency
Estimating techniques
Neural networks
Optimization algorithms
Regression analysis
Studies
Online Access:Get full text
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Summary:In this study, estimation capacities of response surface methodology (RSM) and artificial neural network (ANN) in a heterogeneous photo-Fenton process were investigated. The zeolite Fe-ZSM5 was used as heterogeneous catalyst of the process for degradation of C.I. Acid Red 14 azo dye. The efficiency of the process was studied as a function of four independent variables, concentration of the catalyst, molar ratio of initial concentration of ... to that of the dye (H value), initial concentration of the dye and initial pH of the solution. First, a central composite design (CCD) and response surface methodology were used to evaluate simple and combined effects of these parameters and to optimize process efficiency. Satisfactory prediction second-order regression was derived by RSM. Then, the independent parameters were fed as inputs to an artificial neural network while the output of the network was the degradation efficiency of the process. The multilayer feed-forward networks were trained by the sets of input-output patterns using a backpropagation algorithm. Comparable results were achieved for data fitting by using ANN and RSM. In both methods, the dye mineralization process was mainly influenced by pH and the initial concentration of the dye, whereas the other factors showed lower effects. (ProQuest: ... denotes formulae/symbols omitted.)
ISSN:0013-936X