BP neural network in predicting the nano-titanium dioxide photocatalytic degradation of nitrotoluene wastewater

The Back Propagation(BP) network was trained with the data from the photocatalytic degaration nitrotoluene wastewater treatment experiment and a network model was built for this nitrotolune wastewater treatment process. The nitrotoluene photocatalytic process was stimulated with the trained network model. The correlation degree between network analog output and experimental data of nitrotoluene concentration is 0.998. The photocatalytic degradation nitrotoluence wastewater treatment was predicted with this neural network model. And the correlation degree between network predictive data of and experimental data of nitrotoluene concentration is 0.976. BP neural network model was established to predict the optimal reaction conditions of the photocatalytic degradation process, and the determined conditions are as follows: the mass concentration of TiO₂ is 0.10g/L,the concentration of H ₂O₂ is 0.10 mL/L,and the value of pH is 3.