关键词: 地铁基坑, 数量化理论Ⅲ, 变形影响因素, 耦合强度, BP神经网络

Abstract: In the purpose of assessing objectively the influencing factors of subway foundation pit’s deformation and improving the targeted controlling of pit deformation, we examined the influence degree of various factors using quantification theory III with 30 pit examples as engineering background. We identified the coupling strength among the factors according to sample scores under different conditions and evaluated the accuracy of selecting factors by constructing BP neural network with different input layer conditions. Results revealed leading factors inclusive of permeability coefficient, foundation pit depth, support spacing and embedded depth; important factors, namely, internal friction angle, cohesive force, length of foundation pit, width of foundation pit and groundwater level; and general factors including natural unit weight and stiffness of support structure. The coupling degrees among the influencing factors are mainly at medium and low level. The optimized BP neural network has a higher prediction accuracy than traditional BP neural network, which verifies the accuracy of the quantitative theory III in screening the influence factors of foundation pit deformation. Through this study, the applicability and effectiveness of the quantitative theory III in the analysis of the influence factors of foundation pit deformation are proved, which provides some reference for the deformation control of foundation pit.

Key words: subway foundation pit, quantification theory III, influencing factors of deformation, coupling strength, BP neural network