The Use of Artificial Neural Network (ANN) for Modeling of Ammonia Nitrogen Removal from Landfill Leachate by the Ultrasonic Process

  • Majid Arabameri 1 1 Vice-chancellery for Food and Drug, Shahroud University of Medical Sciences, Shahroud, Iran.
  • Javid Allahbakhsh 2 2 Dept. of Environmental Health Engineering, School of Health, Shahroud University of Medical Sciences, Shahroud, Iran.
  • Aliakbar Roudbari 3* 3 Center for Health-Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran.

Abstract

Background: The study examined the implementation of artificial neural network (ANN) for the prediction of Ammonia nitrogen removal from landfill leachate by ultrasonic process.Methods: A three-layer backpropagation neural network was optimized to predict Ammonia nitrogen removal from landfill leachate by ultrasonic process. Considering the smallest mean square error (MSE), The configuration of the backpropagation neural network was three-layer ANN with tangent sigmoid transfer function (Tansig) at hidden layer with 14 neurons, linear transfer function (Purelin) at output layer and Levenberg–Marquardt backpropagation training algorithm (LMA).Results: ANN predicted results were very close to the experimental results with correlation coefficient (R2) of 0.993 and MSE 0.000334. The sensitivity analysis showed that all studied variables (Contact time, ultrasound frequency and power and pH) had strong effect on Ammonia nitrogen removal. In addition, pH was the most influential parameter with relative importance of 44.9%.Conclusions: The results showed that neural network modeling could effectively predict Ammonia nitrogen removal from landfill leachate by ultrasonic process.
Published
Jan 30, 2016
How to Cite
ARABAMERI 1, Majid; ALLAHBAKHSH 2, Javid; ROUDBARI 3*, Aliakbar. The Use of Artificial Neural Network (ANN) for Modeling of Ammonia Nitrogen Removal from Landfill Leachate by the Ultrasonic Process. International Journal of Health Studies, [S.l.], p. page:13-19, jan. 2016. ISSN 2423-6594. Available at: <http://ijhs.shmu.ac.ir/index.php/ijhs/article/view/81>. Date accessed: 25 may 2020. doi: http://dx.doi.org/10.22100/ijhs.v1i3.81.
Section
Articles

Keywords

Modeling, ANN, Ammonia nitrogen, Leachate, Ultrasound