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Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks
( Vol-5,Issue-3,March 2018 )
Author(s):

Moein Gheytaspour,Omid Habibzadeh Bigdarvish

Keywords:

Yazd treatment plant, chemical oxygen demand, neural networks, sigmoid tangent.

Abstract:

Modeling the wastewater treatment plant is difficult due to nonlinear properties of most of its different processes. Due to the increasing concerns over environmental effects of treatment plants considering the poor operation, fluctuations in process variables and problems of linear analyses, algorithms developed using artificial intelligence methods such as artificial neural networks have attracted a great deal of attention. In this research, first using regression analysis, the parameters of biological oxygen demand, chemical oxygen demand, and pH of the input wastewater were chosen as input parameter among other different parameters. Next, using error analysis, the best topology of neural networks was chosen for prediction. The results revealed that multilayer perception network with the sigmoid tangent training function, with one hidden layer in the input and output as well as 10 training nodes with regression coefficient of 0.92 is the best choice. The regression coefficients obtained from the predictions indicate that neural networked are well able to predict the performance of the wastewater treatment plant in Yazd.

ijaers doi crossref DOI:

10.22161/ijaers.5.3.8

Paper Statistics:
  • Total View : 136
  • Downloads : 20
  • Page No: 050-057
Cite this Article:
MLA
Moein Gheytaspour et al ."Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol 5, no. 3, 2018, pp.050-057 AI Publications, doi:10.22161/ijaers.5.3.8
APA
Moein Gheytaspour,Omid Habibzadeh Bigdarvish(2018).Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks. International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),5(3), 050-057. http://dx.doi.org/10.22161/ijaers.5.3.8
Chicago
Moein Gheytaspour,Omid Habibzadeh Bigdarvish. 2018,"Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks". International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(3):050-057. Doi: 10.22161/ijaers.5.3.8
Harvard
Moein Gheytaspour,Omid Habibzadeh Bigdarvish. 2018,Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks, International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)).5(3), pp:050-057
IEEE
Moein Gheytaspour,Omid Habibzadeh Bigdarvish."Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks", International Journal of Advanced Engineering Research and Science(ISSN : 2349-6495(P) | 2456-1908(O)),vol.5,no. 3, pp.050-057,2018.
Bibtex
@article {moeingheytaspour2018forecasting,
title={Forecasting Oxygen Demand in Treatment Plant Using Artificial Neural Networks},
author={Moein Gheytaspour,Omid Habibzadeh Bigdarvish},
journal={International Journal of Advanced Engineering Research and Science},
volume={5},
year= {2018},
}
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References:

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