Modelling the Performance of Water Treatment Plants Using Artifical Neural Networks - A Literature Review

Annual Conference

Since the 1990s the Artificial Neural Network (ANN) modelling approach has gained popularity for prediction and forecasting due to its ability to capture complex nonlinear relationships. The application of ANNs in the field of water treatment has been somewhat limited to date but the technique could prove to be a powerful tool in creating accurate models for predicting the performance of water treatment plants. In this paper, literature regarding modelling water treatment plant performance or a similar field of study has been assessed with the goal to establish the current state of creating an overall predictive water treatment plant model and identify knowledge gaps. A secondary goal is to establish a best practice for the modelling of water treatment plant performance. Only papers which helped in establishing the current state have been considered and this narrowed the number of assessed papers to 35. Modelling methods other than ANNs have also been reviewed and in conclusion insight has been gained in producing an overall water treatment plant model with model input selection and the generalisation ability being important aspects of the model and model development.

Conference Papers Potable Water Treatment Resource - Conference Papers

17.00 Ivan Ottenheijm - Modelling The Performance Of Water Treatment Plants Using.pdf

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20 Dec 2016