Artificial neural network based models for predicting the effluent quality of a combined upflow anaerobic sludge blanket and facultative pond: Performance evaluation and comparison of different algorithms.

The main objective of this work was to test different artificial neural network (ANN) based models, i.e. the ANN feed forward back propagation (ANN-FFBP), deep feed forward backpropagation (DFFBP), and deep cascade forward back propagation (DCFBP) models, for predicting the effluent quality of an upflow anaerobic sludge blanket-facultative pond (UASB-FP) system.