基于多种优化支持向量机及V/S分析法的隧道变形预测及趋势判断

摘要

隧道变形具有明显的非线性特征,为实现其准确预测,基于卡尔曼滤波和多种优化的支持向量机模型对隧道变形进行预测,以探讨不同预测模型的适用性,并进一步进行组合预测;同时,利用V/S分析法计算变形序列的Hurst指数,以判断隧道的变形趋势,并与预测结果进行对比,综合判断隧道的变形规律.结果表明:最小二乘支持向量机的优化效果最好,且预测隧道后4个周期均为增长变形;同时,变形序列和速率序列V/S分析的Hurst指数分别为0.845和0.602,均＞0.5,得出隧道后期变形呈持续增长趋势,与预测分析一致,验证了思路的有效性.%Tunnel deformation is of obvious non-linear characteristics.In the present research,models based on the Kalman filter and a variety of optimization support vector machines are built for accurate prediction.The applicabili ty of various models is discussed,and further combinatorial prediction is conducted.Meanwhile,V/S analysis is adopted to calculate the Hurst index of deformation series for deformation trend judgment.The judgment result is compared with prediction result in the aim of obtaining the comprehensive deformation rules of tunnel.Results sug gest that the least squares support vector machine has the optimum effect,and the deformation in the next four cy cles would keep increasing.Moreover,the Hurst index of deformation series and deformation rate series is 0.845and 0.602,respectively,both larger than 0.5,indicating that the deformation in late stage would experience a sustained growth,which is consistent with the prediction result.