灰色预测模型在隧道洞顶楔形体稳定性预测中的应用

doi:10.11896/j.issn.1002-137X.2019.05.051

摘要/Abstract

摘要： 目前我国在交通方面投建了大量的基础设施,隧道是其中不可避免的工程,特别是在西部地区。在隧道中,洞顶楔形体失稳是施工中存在的危害之一,对楔形体进行监测和预测以保证隧道施工及后期的安全具有重要的意义。通过预测,施工方能及时采取有效措施来消除危险,避免经济损失和人员伤亡。隧道楔形体失稳的影响因素复杂、影响因子难以量化且具有不确定性,符合灰色系统的特性。将灰色系统理论应用于隧道楔形体变形的预测,在原始监测数据的基础上建立隧道楔形体变形的G(1,1)单点预测模型。通过工程实例,验证了该模型的精度。预测模型中,后验差比为C=0.1195,小误差频率为P=1。结果表明,预测模型的精度达到了较高的水平,该预测的结果可以很好地指导实际施工。

关键词: 单点预测模型, 灰色理论, 灰色预测, 隧道, 楔形体

Abstract: With the construction of a large number of transport infrastructure in China,tunnel engineering is inevitable,especially in the western region.In the tunnel,the stability of the roof wedge is one of the harms existing in the construction.It is of great significance to monitor and predict the wedge to ensure the safety of the tunnel construction and the later period.Through prediction,timely and effective measures are taken to eliminate risks and avoid economic losses and casualties.The influence factors of tunnel wedge instability are complex and difficult to quantify and are uncertain,which accords with the characteristics of grey system.This paper applied the grey system theory to the prediction of tunnel wedge deformation,and established the G(1,1) single point prediction model of tunnel wedge deformation based on the original monitoring data.The accuracy of the model was verified by an engineering example.In the prediction model,the posterior error ratio C is 0.1195 and the frequency of small error P is 1.The results show that the precision of the prediction model reaches a higher level,and the prediction results can guide the actual construction very well.

Key words: Grey prediction, Grey theory, Single point prediction model, Tunnel, Wedge

中图分类号:

TU457

吴发友, 王林峰, 翁其能. 灰色预测模型在隧道洞顶楔形体稳定性预测中的应用[J]. 计算机科学, 2019, 46(5): 327-330. https://doi.org/10.11896/j.issn.1002-137X.2019.05.051

WU Fa-you, WANG Lin-feng, WENG Qi-neng. Application of Grey Prediction Model in Prediction of Stability of Wedge-shaped Body of Tunnel[J]. Computer Science, 2019, 46(5): 327-330. https://doi.org/10.11896/j.issn.1002-137X.2019.05.051

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