This work presents a way to predict the biochemical oxygen demand (BOD) of the output stream of the biological wastewater treatment plant at RIPASA S/A Celulose e Papel, one of the major pulp and paper plants in Brazil. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a backpropagated neural network. The influence of input variables is analyzed and satisfactory prediction results are obtained for an optimized situation.
Artificial neural networks; Principal components analysis; Wastewater treatment and Biochemical oxygen demand
