Elman回归神经网络在大坝安全监控中的应用  

Application of Elman recursive neural network to dam safety monitoring

作　　者：赖道平[1] 顾冲时[1] 

机构地区：[1]河海大学水利水电工程学院,江苏南京210098

出　　处：《河海大学学报（自然科学版）》2003年第3期255-258,共4页Journal of Hohai University(Natural Sciences)

基　　金：国家自然科学基金资助项目(50139030)

摘　　要：给出了Elman回归神经网络的网络结构和学习方法.基于Elman回归神经网络能够逼近任意非线性函数的特点,提出了一种基于Elman回归神经网络建立安全监控模型的方法.实验表明,所建立Elman神经网络模型收敛速度快,并且其拟合及预报精度高于统计模型和BP网络模型.The structure and learning method of the Elman recursive neural network are presented. Based on the fact that the Elman recursive neural network can well approach any nonlinear continuous function, the Elman recursive neural network is adopted to develop a safety monitoring model. Experiments show that the convergence rate of the model developed is high, and that the precision of fitting and prediction by the model is higher than that by the regression model and BP network model.

关 键 词：大坝 安全监控 E1man回归神经网络 神经网络模型 

分 类 号：TV698.19[水利工程—水利水电工程]