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Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring

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Abstract

We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R 2), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events.

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Acknowledgments

The authors wish to thank the Department of Environment for providing the required data for this research. The research was supported by a grant awarded to the second and third authors from University Kebangsaan Malaysia; UKM-GUP-PLW-08-13-308 and FRGS Fund UKM-KK-02-FRGS0125-2009.

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Authors and Affiliations

  1. Department of Engineering Science, Universiti Malaysia Terengganu, Kuala Terengganu, Malaysia

    A. Najah

  2. Department of Civil and Structural Engineering, Universiti Kebangsaan Malaysia, Bangi, Malaysia

    A. El-Shafie & O. A. Karim

  3. Faculty of Engineering, University of Garyounis, Banighazi, Libya

    Amr H. El-Shafie

Authors
  1. A. Najah
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  2. A. El-Shafie
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  3. O. A. Karim
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  4. Amr H. El-Shafie
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Correspondence to A. Najah.

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Responsible editor: Michael Matthies

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Najah, A., El-Shafie, A., Karim, O.A. et al. Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring. Environ Sci Pollut Res 21, 1658–1670 (2014). https://doi.org/10.1007/s11356-013-2048-4

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  • DOI: https://doi.org/10.1007/s11356-013-2048-4

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