人工神经网络在湖泊富营养化评价中的应用研究

Application of Artificial Neural Network to Evaluation of Lake Eutrophication

运用人工神经网络技术评价湖泊富营养化程度。详细阐述了神经网络的结构设计、样本生成及学习算法,给出了通过训练得出的网络权值和阈值,最后将此神经网络用于12个湖泊的富营养化评价,取得了较好的评价结果。

Evaluation of lake eutrophication by means of artificial neural network (ANN) was presented. Design of ANN structure, sample preparation and algorithm learning were discussed in detail. Then the network's weights and threshold value learned by training were put forward. Finally, the neural network has been applied to evaluation of eutrophication in twelve lakes, and achieved good results.