Volume 15, Issue 45 (9-2014)                   Zanko J Med Sci 2014, 15(45): 56-66 | Back to browse issues page

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Salehi K, Shahmoradi B, Maleki A, Mansouri B, Gharibi F. Application of artificial neural network to modeling and optimization of removal of acid black1 using TiO2-Ni nanocoposite. Zanko J Med Sci 2014; 15 (45) :56-66
URL: http://zanko.muk.ac.ir/article-1-37-en.html
Abstract:   (5719 Views)
ABSTRACT
Background and Aim: Artificial Neural Network is non-liner mapping structure based on the function of the human brain. They are powerful tools for modelling, especially when the underlying data relationship is known. So, the aim of this study was the used of artificial neural network to modelling and optimization of removal of acid black1 using TiO2-Ni nanocoposite. 
Material and Methods: This study was an applied research in which TiO2-Ni nanocoposite was synthesized and its chemical properties was evaluated by SEM. For experiments design, predicting, and modeling dye removal were used taguchi method, Artifial Nerual Network (ANNs). 
Result: The results showed that network with tan sigmoid transfer functions, Levenberg –Marquardt algorithm, one hidden layer and four neuron in hidden layer estimated better removal dye of acid black1. 
Conclusion: It is concluded that ANN model can estimate the behavior of the photocatalyst process under different experimental conditions.
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Type of Study: Research | Subject: Special
Received: 2014/08/3 | Accepted: 2014/08/27 | ePublished: 2014/09/16

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