支持向量机在围岩变形监测中的应用  

Application of Support Vector Machine in Rock Deformation Monitoring

作　　者：张彬[1] 李恒[1] 陈江[1] 

机构地区：[1]辽宁工程技术大学土木建筑工程学院,阜新123000

出　　处：《世界科技研究与发展》2011年第3期425-427,共3页World Sci-Tech R&D

摘　　要：根据支特向量机优越的非线性拟合性能,建立变形量的时间序列预测模型,滚动预测围岩变形量,提高了预测模型的训练速度和预测推广能力。该方法用于西乡-固戍盾构段围岩变形预测,并与BP神经网络预测进行比较。结果表明这种模型可预测区间较长且具有较高的准确度,能够科学地指导现场施工和监测。According to the powerful capacity of the support vector machine in non-linear modeling, the time serial forecast model is estab-lished to predict rock deformation continuously. The training and the predictive ability of the forecast model is promoted. The method is used in Xixiang-Gushu Shield segment to predict the rock deformation. Compared with BP neural network, the results show that a longer range and higher accuracy forecast interval can be predicted. So the site construction and monitoring can be guided scientifically by this model.

关 键 词：支持向量机 时间序列 围岩稳定 变形预测 

分 类 号：U456.31[建筑科学—桥梁与隧道工程]