Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis
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.
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Digital revista |
| Language: | English |
| Published: |
Brazilian Society of Chemical Engineering
2002
|
| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322002000400002 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|