doi: 10.7763/IJESD.2012.V3.220
Landfill Leachate Circulation on Old Waste Pretreatment Performance Prediction with Artificial Neural Networks
Mohssen Shoeybi
,
Arman Shafiei Kamel ,
Jonathan L. Salvacion
- the Graduate Studies School of Mapua Institute of Technology, Intramuros, Manila, Philippine
Abstract
Performance of landfill fresh leachate pretreatment by circulation on primitive waste deposits predicted by artificial neural network (ANN) mathematical modeling. Landfill simulation reactor (LSR) for laboratoryscale modeling was applied to prepare the old waste and evaluation of pretreatment performance. Concentration of BOD5 and COD in leachate measured as organic compound indicators and NH3 and NH4 concentrations as nitrogen compounds. The results indicated that organic matters removal (64%) was higher compare to nitrogen compounds removal (42%). Optimized neural network was constructed with a mean absolute error (MSE) of 30.85 and 6-7-4 structure. The input of model was leachate characteristics and time, while the output was removal performance for organic and nitrogen compounds. The R value of 0.979 from regression analyses indicated there was very good agreement in the trends between forecasted and measured data.
Keywords
- Laboratory scale
- landfill simulation reactor
- organic compound
- nitrogen
How to Cite
Mohssen Shoeybi, Arman Shafiei Kamel, and Jonathan L. Salvacion, "Landfill Leachate Circulation on Old Waste Pretreatment Performance Prediction with Artificial Neural Networks," International Journal of Environmental Science and Development, vol. 3, no. 3, pp. 223-227, 2012. https://doi.org/10.7763/IJESD.2012.V3.220
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).