Artificial neural networks: applications in the drinking water sector

Abstract

Artificial neural networks (ANNs) could be used in effective drinking water quality management. This review provides an overview about the history of ANNs and their applications and shortcomings in the drinking water sector. From the papers reviewed, it was found that ANNs might be useful modelling tools due to their successful application in areas such as pipes/infrastructure, membrane filtration, coagulation dosage, disinfection residuals, water quality, etc. The most popular ANNs applied were feed-forward networks, especially Multi-layer Perceptrons (MLPs). It was also noted that over the past decade (2006–2016), ANNs have been increasingly applied in the drinking water sector. This, however, is not the case for South Africa where the application of ANNs in distribution systems is little to non-existent. Future research should be directed towards the application of ANNs in South African distribution systems and to develop these models into decision-making tools that water purification facilities could implement