BP神经网络在渭河水环境质量评价中的应用

Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River

为准确和客观地评价渭河水环境质量状况,将改进算法的BP神经网络引入地表水环境质量评价领域,采用渭河2010年(9月7日至10月11日)水质指标监测数据,构建了渭河水环境质量评价模型。通过3个水质监测项目(氨氮、高锰酸盐指数、溶解氧)对渭河水质进行了评价,评价结果与环境保护部公布结果完全一致。结果表明,BP神经网络应用于水环境质量评价具有客观性、通用性和实用性,可以很好地解决评价因子与水质等级间复杂的非线性关系,评价方法简便可靠,预测精度高。

In order to evaluate the surface water environment quality accurately and objectively,the BP neural network with improved algorithms is introduced in water environmental quality evaluation.Water environment quality evaluation model of the Weihe River was constructed with recorded data of water quality during the period from Sep.7 to Oct.11 in 2010.Water quality of the Weihe River was evaluated through 3 water quality monitoring projects（NH3—N,potassium permanganate index,DO）,and the evaluation results by the BP neural network and by the environmental protection department were compared,and both evaluation results are identical.The results showed that the BP neural network model could well solve complex nonlinear relation between the evaluation factors and water quality levels,and the method was simple and reliable,and the forecast precision was high.The BP neural network for water environmental quality evaluation is objective,universal and practical.