基于RBF神经网络的湖库水质富营养化程度评价模型

MODEL OF ASSESSING LAKE AND RESERVOIR EUTROPHICATION BASED ON RBF NETWORK

运用人工神经网络中的RBF网络算法,建立一种新的湖库水质富营养化程度评价模型。对我国污染差异分布广泛的12个湖库的水质富营养程度评价数据中的10组作为训练样本进行网络的建立,剩余2组用于网络的检验。结果表明:该方法建立的评价模型比文献[1]利用多元统计分析方法建立的评价模型更加简便有效。

A new model of lake and reservoir eutrophication assessment can be established with RBF network of artificial neural network.There are twelve groups of given data,of which ten groups are used to establish network and two groups are used to test the network.The results show that the RBF network is better than the methods of principal component analysis and discriminant analysis in solving the problems of water eutrophication assessment.