Back-Propagation Model for Nanofiltration Process Simulation in Pesticide Wastewater Treatment

Abstract:

Article Preview

This study simulated the nanofiltration (NF) process of contamination removing by back-propagation neural network (BPNN), according to the test values of DK membrane pre-treating Imidacloprid pesticide wastewater. The real time nanofiltration (NF) separation model was presented for effective controlling of DK NF separation. The research showed the simulation precision met the application demands, with the correlation coefficient between the simulation and test rejection of COD and salt over 0.99, and absoluteness error below ±4%. In order to test the prediction of this BPNN simulation model, further NF experiments were carried out. Under the same multifactor condition, the predictions for the NF process performances were found to be in good agreement with the experimental results. This BP simulation model for NF process could be used to test the stability and effectively of NF system, and support the membrane technology well.

Info:

Periodical:

Advanced Materials Research (Volumes 168-170)

Edited by:

Lijuan Li

Pages:

404-407

DOI:

10.4028/www.scientific.net/AMR.168-170.404

Citation:

Q. Yang et al., "Back-Propagation Model for Nanofiltration Process Simulation in Pesticide Wastewater Treatment", Advanced Materials Research, Vols. 168-170, pp. 404-407, 2011

Online since:

December 2010

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.