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

Qing Yang; Yong Ju Hu; Liang Xue

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

Paper Titles

Thermal Degradation of Flame Retardant Cotton Cellulose
p.380

Research on Compressive Stress - Strain Relationship of Fiber Reinforced Concrete
p.384

Experimental Study on Freeze-Thaw Resistance Durablilty of High Performance Concrete
p.393

Construction and Experiment of the Harbin Ice Shell
p.398

Back-Propagation Model for Nanofiltration Process Simulation in Pesticide Wastewater Treatment
p.404

The Impact of Corrosion on the Mechanical Behavior of Bolt
p.408

A Simple Model of Predicting the Degree of Hydration of Concrete Using Artificial Neural Networks
p.412

Analytical Modeling of Flutter Aerodynamic Derivatives for Open-Truss Stiffened Suspension Bridge
p.418

Analysis and Comparison on Mechanical Properties between Full-Graded and Wet-Screened Concretes
p.426

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 168-170Back-Propagation Model for Nanofiltration Process...

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

Abstract:

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.