A SURVEY ON ARTIFICIAL INTELLIGENCE TECHNIQUES FOR VARIOUS WASTEWATER TREATMENT PROCESSES

Authors

  • V. G. Mohan Universiti Malaysia Pahang
  • A. F. M. Ali Universiti Malaysia Pahang
  • B. L. Vijayan Universiti Malaysia Pahang
  • A. Ameedeen Universiti Malaysia Pahang

Abstract


Pollutant removal percentage is a key parameter for every WWTPs, and it is crucial to predict pollutant removal efficiency. The efficiency of pollutant removal processes can be increased with the help of modelling and its optimization. Statistical models are not practical enough for wastewater treatments due to the complicated relationship among input and output parameters. ML models are typically more malleable when modelling non-linear complex datasets with missing data. Many AI techniques are available, and the aim is to investigate the suitable AI technique for designing efficient models for WWTPs. DL and EL are the main techniques reviewed in this work. The EL models show the most successful performance among other techniques by generally showing their accuracy and efficiency.

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Published

2023-06-30

How to Cite

V. G. Mohan, A. F. M. Ali, B. L. Vijayan, & A. Ameedeen. (2023). A SURVEY ON ARTIFICIAL INTELLIGENCE TECHNIQUES FOR VARIOUS WASTEWATER TREATMENT PROCESSES. Journal of Engineering and Technology (JET), 14(1), 29–40. Retrieved from https://jet.utem.edu.my/jet/article/view/6411