Fuzzy Logic-Based Model to Predict the Impact of Flow Rate and Turbidity on the Performance of Multimedia Filters
Author | Hawari Alaa H. |
Author | Elamin Mazen |
Author | Benamor Abdelbaki |
Author | Hasan Shadi W. |
Author | Ayari Mohamed Arselene |
Author | Electorowicz Maria |
Available date | 2020-11-26T10:24:09Z |
Publication Date | 2017 |
Publication Name | Journal of Environmental Engineering (United States) |
Resource | Scopus |
ISSN | 7339372 |
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. |
Sponsor | The authors wish to acknowledge Qatar University for the financial support. |
Language | en |
Publisher | American Society of Civil Engineers (ASCE) |
Subject | Fuzzy logic Multimedia filtration Multiple regression Prediction Treated effluent Wastewater |
Type | Article |
Issue Number | 9 |
Volume Number | 143 |
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Civil & Architectural Engineering [774 items ]
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