隧道洞口边坡变形的多阶段递进预测研究

Study of Multi-stage Progressive Prediction of Slope Deformation of Tunnel Portal

为及时掌握隧道洞口边坡的变形规律,保证隧道进洞过程的安全,采用小波变换剔除变形序列中的误差信息,将原始序列分解为趋势项和误差项序列,并采用PSO-LSSVM模型和ARMA模型分别对趋势项和误差项进行预测,将两者叠加即得到边坡的综合变形预测值,再利用马尔科夫链建立预测误差的修正模型,进一步提高预测精度。对预测模型进行实例分析,结果表明:sym9小波函数、启发式阈值标准、硬阈值选取标准及10层小波分解的去噪效果较优,且通过综合预测,得到边坡变形预测结果的相对误差均值为1. 03%,方差值为0. 042 6,预测精度和稳定性较高,验证了预测模型的有效性。

The deformation rules of slope of tunnel portal should be learned in time and the safety of tunnel portal construction should be guaranteed.Hence,the error information of the deformation sequence is eliminated by wavelet transform and the original sequence is decomposed into trend term sequence and eror term sequence.And then the trend term and error term are predicted by PS0-LSSVM model and ARMA model,respectively;the comprehensive deformation prediction values of slope are obtained by superimposing trend term and error term;and the correction model of prediction eror is established by Markov chain to further improve the prediction accuracy.Finally,a case study is carried out.The study results show that:(1)The denoising effects of sym9 wavelet function,heuristic threshold standard,hard threshold selection criteria and 10-layer wavelet decomposition are better.(2)The average value of relative error and variance value of comprehensive prediction results are 1.03%and 0.042 6,respectively,which indicates the high prediction accuracy,stability and feasibility of the prediction model.