径向基函数网络在湖泊富营养化程度评价中的应用

An application of RBF artificial neural network to the lake eutrophication evaluation

本文建立了一个ＲＢＦ人工神经网络，并探索用于湖泊富营养化程度评价的可行性，同时提出了一种简便、快速的训练ＲＢＦ网络的最小二乘算法（ＲＢＦＬＳ算法）．在１２个湖泊富营养化程度评价中的应用成果表明，本文提出的ＲＢＦ网络及其算法是合理、可行、能用的．

In this paper,a model for evaluating the lake eutrophicaiton has been presented by using a three layer forward radial basis function artificial neural network(RBFANN) and a least squares estimation algorithm for RBFANN(RBF LS algorithm)has been developed.The results of using this model to 12 lakes show that the method possesses reasonability,objectivity,generality and practicality for lake eutrophication evaluation.