Water quality evaluation of surface water based on back propagation neural network

Taking the monitoring data of water quality, of Fenhe River in Shanxi province, as an example, based upon the comprehensive analysis of the monitoring data and standard of water quality, a kind of water quality evaluation model based on artificial neural network is proposed in this paper. This software model adopts the technology of Access to manage foundation database and takes the water quality evaluation criteria as learning samples. With the aid of the artificial neural networks and repeatedly training, as well as self-revision of the network, the BP network model for water quality evaluation with high precision has been obtained and finally realized the intelligence evaluation of water quality which to be evaluated. Practical examples indicated that this kind of evaluation method is very reliable, accurate and highly intellectualized compared with conventional evaluation methods. This new method may meet the synthetic evaluation needs of surface water quality.