In order to study the influence of slurry shield tunneling parameters on surface settlement, based on the slurry shield tunneling and monitoring data of the left line of the Hesong-Heshan stacked section of Harbin Metro Line 3 project, based on the BP neural network optimized by genetic algorithm, the different settlement output forms were studied. The tunnel distance label was introduced to optimize the neural network fitting effect, and the parameter sensitivity analysis was carried out according to this network model. Three most sensitive parameters were obtained, and exhaustive tests were carried out to further analyze the specific influence of parameters on surface settlement. The research shows that the surface settlement performance of slurry shield tunneling is not closely related to the tunneling parameters after passing through a certain ring for two days, and the surface settlement analysis can focus on the monitoring value of the day. Before, during and after the shield machine passes through a certain ring, it will have different effects on the surface settlement above the ring. Subsequent research on surface settlement based on neural network can be considered to include this index. Among the parameters of slurry shield tunneling, reducing slurry viscosity and increasing slurry specific gravity can control surface subsidence, and increasing propulsion speed can reduce the impact of construction on surface subsidence.