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contributor authorAlaa H. Hawari
contributor authorMazen Elamin
contributor authorAbdelbaki Benamor
contributor authorShadi W. Hasan
contributor authorMohamed Arselene Ayari
contributor authorMaria Electorowicz
date accessioned2017-12-16T09:16:22Z
date available2017-12-16T09:16:22Z
date issued2017
identifier other%28ASCE%29EE.1943-7870.0001262.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4240784
description abstractThis 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.
publisherAmerican Society of Civil Engineers
titleFuzzy Logic-Based Model to Predict the Impact of Flow Rate and Turbidity on the Performance of Multimedia Filters
typeJournal Paper
journal volume143
journal issue9
journal titleJournal of Environmental Engineering
identifier doi10.1061/(ASCE)EE.1943-7870.0001262
treeJournal of Environmental Engineering:;2017:;Volume ( 143 ):;issue: 009
contenttypeFulltext


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