Prediction of biological wastewater treatment performance using artificial neural networks

Ethical Clearance Reference Number: 2021FEBEREC-STD- 065

Pre-processing data from published and unpublished previous studies treating biodiesel-, textile-, polymer-, and pulp and paper wastewater using an ABR and EGSB for artificial neural network (ANN) model simulation and developnent.

For ANN problems to be solved, the selection of a suitable learning rate, momentum, the number of neurons from each of the hidden layers and the activation function is crucial. Therefore, the collected data must be prepared in a Microsoft Excel spreadsheet format with input and output columns. A training file is then created with samples of the whole problem domain to select the required parameters. Three data sets are used: a training data set, test data set and validation data set. When the training process takes place, the neural network will be tested against the testing data to determine accuracy, and training will be stopped when the mean average error remains the same for a period of time.