隧洞变形处置措施及变形预测模型构建研究

Research on Deformation Treatment Measures and Deformation Prediction Model Construction of Tunnel

隧洞变形在不能进行准确预测和控制的情况下将严重影响施工进度,并威胁施工人员生命安全和周边环境的稳定性。基于此,笔者针对隧洞变形简要介绍了隧洞变形的机理和影响,并详细说明了一系列变形处置的常见方法和技术,提出了基于极限学习机(Extreme Learning Machine,ELM)的预测模型,以便能够更准确地预测隧洞变形情况。经验证预测模型拟合优度高达0.99,准确度较高,可为隧洞工程提供重要的理论和实践参考。

Tunnel deformation,which cannot be accurately predicted and controlled,will seriously affect the construction progress and threaten the safety of personnel and the stability of the surrounding environment.The mechanism and impact of tunnel deformation are briefly introduced,and the common methods and techniques for handling deformation are explained in detail.A prediction model based on Extreme Learning Machine(ELM)is proposed to predict tunnel deformation more accurately.After verification,the goodness of fit of this model is as high as 0.99,with high accuracy,which is expected to provide important theoretical and practical references for tunnel engineering.