Abstract
Numerous empirical and analytical relations exist between shield tunnel characteristics and surface deformation. Artificial neural networks (ANN) was used to develop predictive relations between the maximum surface settlement and shield tunnel overburdens, shield diameters, thrusts of shield tunneling, advancement rates of shield, fill factors of grouting, cohesive forces, friction angles and compression modules of the soils. So, ANN can become a useful predictive method. With the advantage of ANN in nonlinear problem, the theoretical model to predict the maximum surface settlement is established. The agreement of the measured results with the actual situation of being predicted shows that the proposed model is satisfactory.
Project 50975194 supported by National Natural Science Foundation of China. Project 2007CB714000 supported by National Basic Research Program of China.
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Qiao, J., Liu, J., Guo, W., Zhang, Y. (2010). Artificial Neural Network to Predict the Surface Maximum Settlement by Shield Tunneling. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16584-9_24
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DOI: https://doi.org/10.1007/978-3-642-16584-9_24
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