The long-term structural settlement is one of the key factors on the construction safety of the large-scale integrated transportation hub underground, so it is necessary to monitor and forecast the structural settlement of the whole structure or its important components. Firstly, based on Huangmugang large-scale transportation hub underground in Shenzhen City, the long-term settlement (up to 119 periods after construction) of the 12-axis giant-inclined-column was monitored by the automatic monitoring system. The tendency of the column settlement was analyzed, and the early warning status of the column was evaluated. The monitoring results indicate that after the construction of the inclined column, the long-term settlement fluctuates within a narrow range in the safe state, then changes to the yellow alerting state, and finally has a slight fluctuation between the two states. Then, the back propagation (BP) neural network model and genetic algorithm-BP (GA-BP) neural network model for inclined column settlement were constructed using 109 periods monitoring data, and the cumulative settlement of inclined columns in the following 10 periods was predicted to compare and verify the effectiveness of the two models. The results indicate that compared to the BP neural network model, the predicted values of the GA-BP neural network model are more consistent with the measured values.