节点文献
RBF神经网络在深基坑监测预测中的运用
RBF Neural Networks Applies In Predicting of Monitoring Deep Foundation Excavation
【摘要】 该文简要介绍了RBF神经网络相对于BP神经网络的优点,分析了RBF神经网络的模型和结构。在此基础上通过Matlab编程语言建立了一预测深基坑工程监测项目的重要内容——墙体位移的RBF神经网络模型,经过工程实例验证了该模型的正确性,说明RBF神经网络在对深基坑工程监测项目的预测是可行和有效的。
【Abstract】 The model and structure of RBF neural networks are analyzed. RBF neural networks take advantage ofBP neural networks. By the computer language of Matlab, a module of RBF neural networks that predictsdisplacement, one of the important items in monitoring the deep foundation excavation, is formed. Themodule is verified by the example and proved that the method of using the RBF neural networks in pre-dicting the items of monitoring the deep foundation excavation is practicable and effective.
【关键词】 RBF神经网络;
深基坑工程;
基坑监测;
位移预测;
【Key words】 RBF neural networks; deep foundation excavation; foundation excavation monitoring; displacement prediction;
【Key words】 RBF neural networks; deep foundation excavation; foundation excavation monitoring; displacement prediction;
- 【文献出处】 上海地质 ,Shanghai Geology , 编辑部邮箱 ,2004年02期
- 【分类号】TU753
- 【被引频次】24
- 【下载频次】271