径向基函数网络在平原河网水质评价中的应用

A Radial Basis Function Artificial Neural Network Model for Water Quality Evaluation in Plain River Network

利用MatLab神经网络工具箱构建了径向基函数神经网络(RBF-ANN)模型,并用于平原河网和水库的水质评价.该模型以国家地表水环境质量标准(GB 3838-2002)为依据,随机生成网络的训练样本集,对网络进行学习,并将训练好的网络模型应用于温黄平原河网和境内水库的水质评价.结果表明,基于径向基函数网络的水质评价模型是合理、简便和快速的.

A radial basis function artificial neural network （RBF-ANN） for water quality evaluation of plain river network and reservoir is constructed by using MATLAB program. The RBF-ANN model is trained through the stochastic samples produced by national aquatic environment quality standard （GB 3838-2002）. A case of the Wenhuang plain river network in Taizhou city is studied. The results indicate that the model is reasonable, convenient and effective.