摘要：To ensure the safety of drinking water, understanding the trends of water quality in water resource andto provide a scientific basis for water quality management, a three-layer BP neural network is selected tosimulate and predict six water quality indicators of the outbound of Dahuofang Reservoir. The six waterquality indicators are dissolved oxygen, five days’ biochemical oxygen demand, permanganate index, ammonianitrogen, total nitrogen and total phosphorus. Training the model with water quality data from 2005 to 2011,Levenberg-Marguardt optimization algorithm is adopted to train samples.After reaching the error requirement,simulate the model with the water quality monitoring data in 2012 and test the model accuracy. Simulationresults show that the accuracy of the model prediction is higher in 2012. It is proved that this model can beused to predict water quality of the outbound mouth in Fushun section, and the model provides a theoreticalbasis for improving the water quality of the reservoir area and can be used to guide the actual water qualitymanagement..
