# Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review
## 7 Conclusions  
Over time, judging the complex mechanical properties of a discontinuous and non-uniform rock mass becomes increasingly difficult. Laboratory experiments and field measurements alone cannot accurately reflect the actual construction process or the dynamic feedback it generates. In response to the demand for production and construction, and the proposal of the New Austrian method, scholars have begun using the changing trend of monitoring surrounding rock displacement to deduce the properties of rock and soil. As a result, the back analysis method has become an effective means of determining the parameters of calculation models. This paper briefly summarizes the reasons for the formation of back analysis methods and introduces the development process of traditional and intelligent back analysis methods. It then summarizes the traditional and intelligent back analysis of three target unknowns: initial ground stress, load of supporting structures, and characteristic parameters of surrounding rock. The main conclusions are as follows:  
1. The back analysis method for initial ground stress is becoming increasingly intelligent and informationized due to the continuous improvement and updating of computer function, as well as the rapid development of neural network and machine learning algorithms. The back analysis method is constantly adjusted and optimized according to the tunnel and underground environment under different geological conditions, and the analysis method suitable for the construction method and construction condition of the project is selected. This ensures a seamless connection between the initial geostress back analysis principle and the actual engineering, and improves the practicability and reliability of numerical analysis methods;
2. The accuracy of back analysis of the load of supporting structures largely depends on the deformation data monitored in the field. Compared to the other two kinds of unknowns, the back analysis of this kind has stronger practical significance and can directly reflect the reliability of engineering design. It also contains fewer uncertain factors and assumptions, which makes the back analysis results more well-posed and reliable;
3. The inversion of tunnel-surrounding rock characteristic parameters is highly ill-posed. To improve the inversion results, more optimization algorithms are needed to analyze unfavorable factors that affect the solution's uniqueness and identifiability. Research methods for this kind of problem are abundant, and the achievements are significant. Currently, the characteristic parameters are obtained by comparing field data with the theoretical model information. With the continuous innovation of computer technology and intelligent calculation methods, and the improvement of field observation accuracy, the inversion results of surrounding rock parameters can be more in line with engineering practice.  
[PERSON], [PERSON] and [PERSON] development the ideas, designed the research methodology. Z.Y. wrote the original version. [PERSON] supervised the work, acquired the funds, planned the research and revised the manuscript. All authors have read and agreed to the published version of the manuscript.  
The funding support was provided by Shaanxi Innovation Capacity Support Program-Innovation Team (No. 2020 TD-005), the Natural Science Foundation of Shaanxi Province (No. 2021 JM-373).  
No applicable.  
The conclusions used to support this review can be obtained from the corresponding authors as required.  
The authors declare no conflict of interest.