摘要
建立了大坝安全监测数据处理坝段挠度预测的径向基神经网络模型 ,与通常的BP神经网络模型进行对比 ,并与实测结果进行校核 .结果表明 ,对于所研究的问题 ,径向基函数网络避免了BP网络的局部极小及收敛速度慢等缺点 ,在精度。
A radial basis function neural network model to data processing technique of dam safety monitoring is established. The prediction model based on radial basis function network is studied through experimental data and verified by additional data successfully. Another network model based on back propagation network is also trained for comparision . The results show that the radial basis function network is much better than back propagation network in accuracy and speed of training for the problem studied.
出处
《武汉大学学报（工学版）》
CAS
CSCD
北大核心
2003年第2期33-36,共4页
Engineering Journal of Wuhan University
关键词
径向基
人工神经网络
大坝安全监测
radial basis function
artificial neural network
dam safety monitoring
