TY - JOUR
T1 - Fuzzy Logic-Based Model to Predict the Impact of Flow Rate and Turbidity on the Performance of Multimedia Filters
AU - Hawari, Alaa H.
AU - Elamin, Mazen
AU - Benamor, Abdelbaki
AU - Hasan, Shadi W.
AU - Ayari, Mohamed Arselene
AU - Electorowicz, Maria
N1 - Funding Information:
The authors wish to acknowledge Qatar University for the financial support.
Publisher Copyright:
© 2017 American Society of Civil Engineers.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - 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.
AB - 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.
KW - Fuzzy logic
KW - Multimedia filtration
KW - Multiple regression
KW - Prediction
KW - Treated effluent
KW - Wastewater
UR - http://www.scopus.com/inward/record.url?scp=85024867089&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)EE.1943-7870.0001262
DO - 10.1061/(ASCE)EE.1943-7870.0001262
M3 - Article
AN - SCOPUS:85024867089
SN - 0733-9372
VL - 143
JO - Journal of Environmental Engineering
JF - Journal of Environmental Engineering
IS - 9
M1 - 04017065
ER -