摘要
在分析影响地下水位动态的诸多因素的基础上,在RBF网络的基础上建立地下水的水位动态预测模型.通过Matlab语言用计算机预测了地下水位动态,计算结果表明:与模糊识别法相比,RBF神经网络模型不仅计算精度很高,同时泛化能力也很强强等特点,能够正确反映地下水位动态变化,是一种值得推广的地下水位动态预测神经网络模型.
On the foundation of analyzing many factors of impacting groundwater level dynamic,establishing groundwater level dynamic forecasting model based on RBF network. Dynamic prediction of groundwater level was carried out with computer by Matlab language, the prediction result indicated： compared with the fuzzy identification method, RBF neural network model has high accuracy and generalization ability,and can reflect the groundwater level dynamic change correctly, it is a groundwater level dynamic forecasting neural network model worthy of to promote.
出处
《内蒙古民族大学学报（自然科学版）》
2012年第6期654-657,共4页
Journal of Inner Mongolia Minzu University：Natural Sciences
