Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: A critical review
This paper critically reviews all artificial intelligence (AI) and machine learning (ML)
techniques for the better control of membrane fouling in filtration processes, with the focus
on water and wastewater treatment systems. Artificial neural networks (ANNs), fuzzy logic,
genetic programming and model trees were found to be four successfully employed
modeling techniques. The results show that well-known ANNs such as multilayer perceptron
and radial basis function can predict membrane fouling with an R 2 equal to 0.99 and an …
techniques for the better control of membrane fouling in filtration processes, with the focus
on water and wastewater treatment systems. Artificial neural networks (ANNs), fuzzy logic,
genetic programming and model trees were found to be four successfully employed
modeling techniques. The results show that well-known ANNs such as multilayer perceptron
and radial basis function can predict membrane fouling with an R 2 equal to 0.99 and an …
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