摘要
利用径向基函数(RBF)神经网络,建立复合地基承载力预测模型,有效解决复合地基承载力预测中的非线性问题.以历史数据为依据,对所建立的RBF神经网络预测模型进行模拟和检验.实例结果表明:应用RBF神经网络所建立的复合地基承载力预测模型,能真实地表达要素之间的高度非线性关系,具有较高的预测精度和较强的实际应用价值.
The nonlinear problems of bearing capacity of composite foundation for prediction was solved effectively by using radial basis function （RBF） neural network and establishing the forecast of bearing capacity of composite foundation model. According to historical data, we carry out the simulation and experiment of RBF neural network predictive model. The results show that the application of RBF neural network in the forecast of bearing capacity of composite foundation model can truly express between elements of the highly nonlinear relationship, has high accuracy and strong practical value.
出处
《河南科学》
2011年第9期1091-1093,共3页
Henan Science
关键词
RBF神经网络
复合地基
承载力
RBF neural network
composite foundation
bearing capacity
