摘要
通过对边坡位移历史数据序列进行特征分析 ,计算出饱和嵌入维数和最大 Lyapunov指数 ,给出了边坡位移的最大可预报时间尺度。在此基础上 ,确定了神经网络的输入节点数 ,建立了基于自适应神经网络的边坡位移预报方法 .通过对三峡升船机高边坡和新滩滑坡实际位移数据进行预测 ,结果令人满意 .这对于建立边坡位移的实时监测
By the characteristic analysis of slope displacement time series, the largest Lyapunov exponent and saturation inseted dimension are obtained, and the longest forecast time is given. On this base, the number of inputing node of neural network is given, moreover, the method of forecasting slope displacement is presented based on adaptive neural network. Through the slope displacement forecasting of the Three Gorges Project list slope and Xintan slide, the results are satisfied. And this has much meaning to established slope displacement forecast-timely.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2001年第12期124-129,共6页
Systems Engineering-Theory & Practice