The Modeling of Petrochemical Wastewater Activated Sludge System and Water Quality Forecast Based on Neural Network

Article Preview

Abstract:

Aiming at the petrochemical wastewater activated sludge system, using the Elman neural network modeling technology, through the improvement structure to improve the dynamic performance of the network, check and repair etc data preprocessing methods, combined with object characteristics selected input variable, construct the neural network model. The simulation results show that the neural network based on the activated sludge system model has good convergence and prediction accuracy, and can meet the control sewage treatment system reliable and stable operation of the engineering application demand.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 641-642)

Pages:

219-222

Citation:

Online since:

January 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Jiang Yunchao, Nan Zongren, Uncertain type water quality model and research progress. Environment Pollution and Control, 2007, 29(9), 713-715.

Google Scholar

[2] J. P. Reed, D. devlin, S.R.R. Esteves, R. dinsdale, A.J. Duwy, Performance parameter prediction for sewage sludge digesters using reflectance FT-NIR spectroscopy, Water Research 45(2011)2463-2472.

DOI: 10.1016/j.watres.2011.01.027

Google Scholar

[3] Song Jun, Yang Ling, Jin Qiang, Based on the improved ELman network soft sensor modeling method , Computer Engineering and Applications44(2008)233-235.

Google Scholar

[4] C. Kriger., and R. Tzoneva, member, IEEE, Neural Networks for Prediction of Wastewater Treatment Plant Influent Disturbance.

DOI: 10.1109/afrcon.2007.4401646

Google Scholar