# A Review of Deep Learning Applications in Tunneling and Underground Engineering in China
## 3 Intelligent Application of Deep Learning in Tunnel Engineering
### Subsea Tunnel  
To solve the traffic problems between the straits and bays, the subsea tunnel was created under conditions without prejudice in terms of ship navigation. Different from the mountain tunnel and the urban subway tunnel. The subsea tunnels are less susceptible to the effects of weather and climate change and have a more stable and smooth passage. It is easy to connect with traffic at both ends to form a road network. Currently, there are four ways to build subsea tunnels in the world, as shown in Table 1.  
However, the construction period of the subsea tunnel is long, and the pore water pressure of the overlying strata of the tunnel is significant, which reduces the arching effect of the surrounding rock. Compared with the other two types of tunnels, the construction environment is qualitatively different. So, it is impossible to obtain geological information via the general survey method. In addition, the longitudinal design section of the tunnel is V-shaped; relying on the tunnel's structure is insufficient for be natural drainage. Once the water inflow is too large, the risk of disasters in the tunnel construction process will greatly increase. During the operation of the subsea tunnel, the infinite water exerts massive pressure on the top of the tunnel, which leads to tunnel leakage becoming the most serious problem. The occurrence of lining cracks will destroy the whole tunnel structure in a short time, and it is prone to collapse water inrush and other disastrous accidents.  
Because of the characteristics of the subsea tunnel and the many complex properties of rock mass, researchers need to consider different boundary conditions, load types, and material characteristics parameters when analyzing them. Therefore, the key to constructing the subsea tunnel is four-fold [78]: (1) the determination of the minimum rock cover thickness; (2) the determination of the design value of water pressure; (3) the optimization of a cross-section of lining structure; and (4) the anti-drainage plan and construction measures for unfavorable sections. Thus, in the analysis of subsea tunnels, it is most significant to determine the stability of the tunnel lining structure, the erosion problem of surrounding seawater seepage caused by excavation, and the risk prediction of water inrush.  
In the past, most methods to solve this kind of problem used numerical analysis and theoretical analysis. These methods require the constant modification and fitting of parameters, which makes the construction very complicated. Compared with land tunnels, the implementation of geological exploration and monitoring control is more complex, and the accuracy of the obtained mechanical parameters is worse. Once the mechanical parameters are inaccurate, bottlenecks will appear in the calculation process. Moreover, it is harder to collect images from outside the subsea tunnel than from inside, and the accuracy of images makes them difficult to use for practical analysis. In addition, there are only a few undersea tunnels built in the world, so CNN, RNN, and other models cannot be effectively used for tunnel lining disease identification and deformation prediction. Con  
\begin{table}
\begin{tabular}{c c} \hline
**Construction Method** & **Application of Tunnel** \\ \hline Drilling and blasting method; buried excavation construction & Xiamen Xiang’an Subsea Tunnel; Qingdao Jiaozhou Bay \\  & Subsea Tunnel \\   Prefabricated pipe section sinking method & Seabed immersed tunnel of Hong Kong-Zhuhai-Macao Bridge \\   Full-section excavation method based on & The Channel Tunnel \\   shield tunneling machine & Tokyo Bay Subsea Tunnel in Japan \\ Full-section pressurized roadheader construction method & \\ \hline \end{tabular}
\end{table}
Table 1: Methods of harbor tunnel construction.  
sequently, combining the deep network optimization algorithm with numerical analysis, using intelligent parameter inversion analysis is a more effective solution.