In order to achieve effective control of papermaking wastewater,improve the environmental protection production capacity of papermaking enterprises. Based on the main components of paper production wastewater,a set of backpropagation neural network models based on temperature,pH,influent COD and influent flow were established,and the effluent COD and gas production of the papermaking process were output through the network. In order to realize the multi-objective optimization of papermaking wastewater,the NSGA-Ⅱ algorithm was introduced on the basis of the backpropagation neural network model,and finally a set of multi-objective wastewater treatment optimization models were formed. In order to verify the effectiveness of the multi-objective wastewater treatment optimization model,the two indicators of effluent COD and gas production were predicted based on the wastewater composition data provided by papermaking enterprises,and it was found that the prediction results output by the model were close to the real value,which was suitable for the anaerobic treatment of papermaking wastewater and had certain application value.
维普
万方数据