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Fuzzy-logic modeling of Fenton’s strong chemical oxidation process treating three types of landfill leachates

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Abstract

Three multiple input and multiple output-type fuzzy-logic-based models were developed as an artificial intelligence-based approach to model a novel integrated process (UF–IER–EDBM–FO) consisted of ultrafiltration (UF), ion exchange resins (IER), electrodialysis with bipolar membrane (EDBM), and Fenton’s oxidation (FO) units treating young, middle-aged, and stabilized landfill leachates. The FO unit was considered as the key process for implementation of the proposed modeling scheme. Four input components such as H2O2/chemical oxygen demand ratio, H2O2/Fe2+ ratio, reaction pH, and reaction time were fuzzified in a Mamdani-type fuzzy inference system to predict the removal efficiencies of chemical oxygen demand, total organic carbon, color, and ammonia nitrogen. A total of 200 rules in the IF–THEN format were established within the framework of a graphical user interface for each fuzzy-logic model. The product (prod) and the center of gravity (centroid) methods were performed as the inference operator and defuzzification methods, respectively, for the proposed prognostic models. Fuzzy-logic predicted results were compared to the outputs of multiple regression models by means of various descriptive statistical indicators, and the proposed methodology was tested against the experimental data. The testing results clearly revealed that the proposed prognostic models showed a superior predictive performance with very high determination coefficients (R 2) between 0.930 and 0.991. This study indicated a simple means of modeling and potential of a knowledge-based approach for capturing complicated inter-relationships in a highly non-linear problem. Clearly, it was shown that the proposed prognostic models provided a well-suited and cost-effective method to predict removal efficiencies of wastewater parameters prior to discharge to receiving streams.

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Acknowledgments

This study was carried out within the scope of 109Y285 number of the research of TUBITAK. We would like to thank TUBITAK that provided the financial support of it.

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  1. Department of Environmental Engineering, Faculty of Civil Engineering, Yildiz Technical University, 34220, Davutpasa, Esenler, Istanbul, Turkey

    Hanife Sari, Kaan Yetilmezsoy, Fatih Ilhan, Senem Yazici, Ugur Kurt & Omer Apaydin

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  1. Hanife Sari
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  2. Kaan Yetilmezsoy
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  3. Fatih Ilhan
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  4. Senem Yazici
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  5. Ugur Kurt
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Correspondence to Hanife Sari.

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Sari, H., Yetilmezsoy, K., Ilhan, F. et al. Fuzzy-logic modeling of Fenton’s strong chemical oxidation process treating three types of landfill leachates. Environ Sci Pollut Res 20, 4235–4253 (2013). https://doi.org/10.1007/s11356-012-1370-6

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