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Modeling of shield-ground interaction using an adaptive relevance vector machine

机译:使用自适应相关矢量机的盾构与地面相互作用建模

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摘要

Shield tunneling method is widely adopted in tunneling projects. Analysis of ground settlement is required as an effective way for minimizing the potential damage caused by tunneling. Many efforts have been devoted for this purpose using various methods such as empirical approaches and numerical modeling. However, there are multiple factors that may influence the ground settlement, and the shield-ground relationship is highly non-linear and complex. To understand the complex soil behavior in response to shield penetration, a model that can establish the relationship and make accurate predictions for tunneling-induced ground settlement is needed. This paper proposed a model based on relevance vector machines (RVMs) to develop the predictive relations. Adaptive feature scaling factors were introduced as an inherent mechanism that enables RVMs to identify the relative importance of each input factor, and an optimization method for obtaining the appropriate values of feature scaling factors is proposed. The potential of the proposed adaptive model was investigated by applying it to tunnels that bored by an earth pressure balance (EPB) shield machine. Three categories of factors, namely tunnel geometry, geological conditions and shield operational parameters were considered in the model. The results demonstrate that the proposed model has competitive predictive capacities and that the adoption of adaptive feature scaling factors can enhance the prediction accuracy and provide a measure of the relative importance of each input factor. Moreover, the implementation of the adaptive RVM model is relatively simple. There is no need to set model parameters because they can be automatically optimized during model training, which makes the method a practical tool for geotechnical engineers to evaluate ground reactions during tunnel excavation.
机译:盾构法在隧道工程中被广泛采用。需要对地面沉降进行分析,将其作为最大程度地减少隧道造成的潜在损害的有效方法。为此,已经使用各种方法,例如经验方法和数值模型,进行了许多努力。但是,有多种因素可能会影响地面沉降,并且屏蔽层与地面之间的关系是高度非线性和复杂的。为了了解响应盾构穿透的复杂土壤行为,需要一个可以建立关系并对隧道引起的地面沉降进行准确预测的模型。本文提出了一种基于相关向量机(RVM)的模型来建立预测关系。引入了自适应特征缩放因子作为使RVM识别每个输入因子的相对重要性的内在机制,并提出了一种用于获取适当的特征缩放因子值的优化方法。通过将其应用到由土压平衡(EPB)盾构机掘进的隧道中,研究了所提出的自适应模型的潜力。该模型考虑了三类因素,即隧道几何形状,地质条件和盾构运行参数。结果表明,所提出的模型具有竞争性的预测能力,自适应特征缩放因子的采用可以提高预测准确性,并提供每个输入因子相对重要性的度量。此外,自适应RVM模型的实现相对简单。无需设置模型参数,因为可以在模型训练期间自动优化模型参数,这使该方法成为岩土工程师评估隧道开挖过程中地面反应的实用工具。

著录项

  • 来源
    《Applied Mathematical Modelling》 |2016年第10期|5171-5182|共12页
  • 作者单位

    School of Resource and Civil Engineering, Wuhan Institute of Technology, Wuhan 430073, PR China,Department of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, PR China, 693 Xiongchu Avenue, Wuhan Institute of Technology, Wuhan 430073, PR China;

    School of Resource and Civil Engineering, Wuhan Institute of Technology, Wuhan 430073, PR China;

    Department of Civil Engineering, Wuhan University of Science and Technology-City College, Wuhan 430083, PR China;

    Changjiang River Scientific Research Institute, Wuhan 430010, PR China;

    Changjiang River Scientific Research Institute, Wuhan 430010, PR China;

    Department of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Ground settlement; Shield-ground interaction; Relevance vector machine; Adaptive feature scaling factors; Instrumentation;

    机译:地面沉降;屏蔽层与地面的相互作用;相关向量机;自适应特征缩放因子;仪器仪表;

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