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A long-span stadium roof has always been a wind load sensitive system, given its usual complex curved surface. However, there is no definite method for calculating the wind load shape factor of the complex building in the code. Based on this, the standard [Formula: see text] model was applied to the computational fluid dynamics numerical simulation of a long-span stadium roof at the wind attack angles of 0°–180°. The pressure distribution on the top and bottom surfaces of the stadium roof and the wind load shape factor were obtained by numerical simulation. The results show that the negative pressure was dominant on the top surface of the roof and the positive pressure was dominant on the bottom surface of the stadium at the wind attack angle of 0°. The ring-shaped curtain wall made the wind field environment more complicated, mainly under the wind attack angles of 45° and 180°. Because of the dip angles at both ends of the roof, the wind pressure distribution at both ends of the roof was opposite to the main region. The maximum wind load shape factors of each region were negative. In addition, the maximum wind load shape factor was at 45°, which was −1.1. The maximum wind load shape factors in regions of R13–R19 were larger, which should be paid attention in design stage. In general, the wind load shape factors were large in the central region and small at both ends. The wind load shape factors of the roof were bounded by 90°, showing an anti-symmetric trend.

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During the shield construction of Harbin Subway Line No. 3 Project, the average ground settlement exceeds the warning value. In order to find the cause of settlement and improve it, this paper establishes a settlement prediction model to analyse the potential influencing factors based on the Deep Belief Network (DBN) and calculated the correlation degree between influencing factors and settlement through sensitivity analysis. It was found that the permeability coefficients of layer and cutter head torque are the main factors affecting settlement. Then, corresponding muck improvement measures were made according to the analysis of the layer conditions, which successfully reduced the permeability and shear strength of the muck, thereby controlling the surface settlement value within the warning range. The research results in this paper illustrate the applicability and robustness of DBN in tunnel engineering, and the related research ideas can be applied to other projects.