人工神经网络在水环境质量评价中的应用

应用人工神经网络理论与方法建立了滏阳河水质评价的RBF(径向基函数)神经网络模型，对滏阳河邯郸市区段的从南环到北环的7个监测断面水质进行了评价，并与灰色聚类结果进行对比。结果表明RBF神经网络模型能很好地解决评价因子与水质等级间复杂的非线性关系，评价水质简便可靠，预测精度高，具有通性和客观性。根据评价结果，分析了滏阳河邯郸市区段水质污染程度，可以为水环境保护工作提供防治依据。

Application of Artificial Neural Network in Water Environmental Quality Assessment

A RBF(Radial Basis Function) neural network model for water quality assessment of Fuyang River is set up by applying artificial neural network theory and method,by which water quality of 7 sections of Fuyang River is evaluated and the results are compared to gray clustering method.The result indicates that RBF neural network model can well resolve complicated nonlinear relation between evaluation gene and water quality grade,and the method is convenient,reliable and precise,so it can be used commonly and objectively.And according to the results of evaluation,contamination degrees of Fuyang River are analyzed,which can offer preventive measures for water environmental protection.