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    Fuzzy Logic-Based Model to Predict the Impact of Flow Rate and Turbidity on the Performance of Multimedia Filters

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    Date
    2017
    Author
    Hawari Alaa H.
    Elamin Mazen
    Benamor Abdelbaki
    Hasan Shadi W.
    Ayari Mohamed Arselene
    Electorowicz Maria
    ...show more authors ...show less authors
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    Abstract
    This paper uses fuzzy logic-based models to predict and evaluate the performance of multimedia filters utilized in wastewater treatment. A fuzzy logic-based model is constructed and trained to predict the operating time (i.e., treated volume of water) of a multimedia filter. A preset acceptable turbidity value of 5 nephelometric turbidity units (NTU) is used as the breakthrough point. The model is based on a set of experimental data with variable flow rates and influent turbidity. The results from the fuzzy-based model indicate that the simulated treated volume at different inputs of turbidity and flow rate fits the experimental results with a coefficient of multiple determination (R2) of 91.6%. To examine the efficiency of the developed model predicting treated volume, the results obtained from the model are compared with the results obtained from a multiple linear regression model. The accuracy of prediction of both models are examined using the mean absolute error (MSE), root-mean-square error (RMSE), and R2. The MSE, RMSE, and R2 for the fuzzy-based model are 5,318, 72.92, and 98%, respectively, whereas for the regression model they are 3,302, 57.46, and 99%, respectively. Although the regression model appears to be more accurate, the fuzzy-based model is deemed to be more advantageous because it can incorporate the uncertainties in inputs as a result of human judgments and can indicate the errors in the outputs. 1 2017 American Society of Civil Engineers.
    DOI/handle
    http://dx.doi.org/10.1061/(ASCE)EE.1943-7870.0001262
    http://hdl.handle.net/10576/17083
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    • Civil and Environmental Engineering [‎862‎ items ]
    • GPC Research [‎502‎ items ]

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