水质综合评价的人工神经网络模型

 为探讨水质综合评价的客观方法，以成都市金堂县东风水库水质资料为例，建立了地面水水质综合评价的BP网络和Hopfield网络模型。BP网络模型以单输出代替多输出可保证评价结果的唯一性。Hopfield网络更优于BP网络，既适用于定量指标的水质参数又适用于定性指标的水质参数，而且使水质评价形象化

The models of artificial neural networks for comprehensive assessment of water quality.

Based on data of the water quality from Dongfeng reservoir in Jintang County,Chengdu City,a method of artificial neural networks BP and Hopfield neural networks is presented for comprehensive assessment of water quality.In the BP network model,multi unit of output that is employed by other researchers is substituted by single unit output.The result derived from the BP neural network is unique.By investigation,the Hopfield neural networks is better than BP neural networks,it is applied to assess water quality because the former is not only suitable to quantitative water components but also suitable to qualitative ones.