RBF神经网络模型在边坡监测中的应用  

Application of RBF neural network model in side slope monitoring

作　　者：高会强[1] 

机构地区：[1]中交四航工程研究院有限公司,广东广州510230

出　　处：《水运工程》2010年第10期135-137,149,共4页Port & Waterway Engineering

摘　　要：在matlab环境下建立了边坡位移预测的RBF神经网络模型。利用已有的监测数据训练神经网络并进行测试,将训练好的网络模型用于预测边坡位移的变化值。最后将该预测方法用于斯里兰卡某边坡监测工程,预测结果与实测的监测数据相比误差较小,从而合理安排监测频次,提高了监测效率。The monitoring of slope is significant to guide the construction of a project.Under the environment of matlab,we established the RBF neural network to forecast the slope displacement.Using the existing monitoring data,the neural network was trained and tested.And then the trained network was applied to forecast the relationship between the slope displacements and time.The system was used in the slope monitoring of Sri Lanka.There was only a minute difference between the forecasted result and the monitoring data.By arranging properly the monitoring frequency,the monitoring efficiency was improved.

关 键 词：边坡监测 位移 RBF神经网络 

分 类 号：U656.3[交通运输工程—港口、海岸及近海工程]