# Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review
## 6 Problems and Prospects of Inversion Analysis Method
To a large extent, it needs to rely on the expert system to make the final decision, and a lot of human and financial resources will be spent on data mining, collection, and storage in this process. With the increasing trend of cross-disciplinary fields, the intelligent back analysis method has proven to be highly effective in solving tunnel engineering problems. However, this method does not solely depend on neural networks or optimization algorithms; instead, neural networks serve as a foundational component. Based on this theory, we can consider the following four aspects to realize diverse intelligent back analysis methods, improve the premature convergence of optimization algorithms, and enhance the reliability of inversion results. The main results are as follows:  
1. Once the autonomous learning process is established, the inversion computing model can actively understand data and make decisions in complex environments. By combining advanced geological prediction, remote sensing, and the use of electromagnetic or waveform signals, monitoring methods can be improved and optimized to make data analysis more accurate and speed up inversion analysis;
2. To better consider tunnel and underground engineering characteristics and find solutions to problems encountered in engineering practice, we should not be limited to relying on various complex optimization algorithms to obtain accurate inversion results. Optimization algorithms are only one of many excellent tools that need to cooperate with engineering practice to realize their practical value. No matter how accurate a tool is, if it does not match its work, it will not be able to maximize its benefits;
3. By combining numerical analysis software with better flexibility, compatibility, and visualization, as well as simulation technology and intelligent technology with BIM technology, machine learning, computer vision, and other means, the inversion process can expand in the interactive direction, gradually moving from bottom to top applications;
4. Using deep learning to enhance the recognition ability of traditional algorithms for object features under complex structures can investigate the root cause. Intelligence aims to achieve a better imitation of the way of thinking and expression of the human brain, and inversion analysis aims to obtain the predicted results more easily. Real intelligence can obtain the final result without relying on a large amount of data, but it still has to be supported by a large amount of data, meaning that the optimization algorithm of intelligent inversion must be established in a new round;
5. The deep learning network structure should strengthen the expandability of use. Most of the network structures, including fully connected neural networks, convolutional neural networks, and cyclic neural networks, are mainly for supervised learning, which is often limited by artificially labeled sample feature information in the process of use and unable to mine deeper feature information. On the other hand, the unsupervised learning network structure, such as generative countermeasure neural networks, has the ability to extract key information from a large amount of unmarked data and has great potential for development. The use of this kind of network structure can be increased when using intelligent back analysis methods to solve tunnel and underground engineering problems in the future;
6. To achieve a breakthrough in tunnel construction and underground traffic design and construction technology with super-long buried depth under complex conditions, it is necessary to further strengthen countermeasures for large deformation and strong erosion and optimize construction equipment in harsh geological environments. In the process of urban rail transit construction, it is necessary to refine the construction management system, improve the efficiency of network operation and maintenance, and form new construction mode ideas to complete the innovation of tunnel engineering technology and inversion theory.