最小二乘支持向量机在隧道围岩变形预测中的应用

针对基于标准型支持向量机(Vapnik SVM)的岩体变形预测方法计算复杂度大、应用不便的缺点,提出一种基于最小二乘支持向量机的围岩变形预测方法.该方法结合开挖岩体具有高度不确定性的特点,将其作为一个时变系统考虑,首先采用滑动时窗方式选取学习样本,然后利用获得的样本训练最小二乘支持向量机预测模型.利用这种方法对雪家庄隧道围岩变形进行预测,分析结果表明,该方法具有较高的预测精度,是一种简单可行的变形预测方法.

Predicting Deformations of Tunnel Surrounding Rock by Using Least Squares Support Vector Machine

In order to overcome the disadvantages of high computational complexity and inconvenience when forecasting deformations of surrounding rock by using support vector machine of standard form(Vapnik SVM),a new deformation prediction method based on least squares support vector machine(LS-SVM) was presented.By using this method,the excavated rock mass was regarded as a time-dependent system with high uncertainty and a sliding time window was employed first to select learning examples,then the examples obtained ...