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This paper presents the development of fuzzy logic (FL) model to predict wastewater effluent at Kerteh Refinery Wastewater Treatment Plant (KR1 IETS). By using historical data from industry that comprising of 22 input and 5 output parameters including chemical oxygen demand (COD), oil and grease content (O&G), total suspended solid (TSS), effluent pH and phenol concentration, two methods were employed: Mamdani and Sugeno to develop the FL model. Using different combination of membership function (MF) the overall and individual output predictions by both methods were analysed and compared using statistical methods. From the results, Sugeno method perform better compared to Mamdani. Testing the model using new data shows that using Sugeno’s method able to predict the output with 73.91% of the prediction accuracy.

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Fuzzy Logic Model for Industrial Wastewater Effluent Prediction: A Case Study at KR1 IETS

  • 会议论文

  • 发表日期：

    2025年

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  • A. F. Ahmad Faudzi,
  • M. R. Othman,
  • H. Mustapa

摘要

This paper presents the development of fuzzy logic (FL) model to predict wastewater effluent at Kerteh Refinery Wastewater Treatment Plant (KR1 IETS). By using historical data from industry that comprising of 22 input and 5 output parameters including chemical oxygen demand (COD), oil and grease content (O&G), total suspended solid (TSS), effluent pH and phenol concentration, two methods were employed: Mamdani and Sugeno to develop the FL model. Using different combination of membership function (MF) the overall and individual output predictions by both methods were analysed and compared using statistical methods. From the results, Sugeno method perform better compared to Mamdani. Testing the model using new data shows that using Sugeno’s method able to predict the output with 73.91% of the prediction accuracy.