## 1 Introduction  
In recent years, the highway construction, water conservancy, hydropower stations, nuclear power stations, and other large-scale projects in China have increased [1; 2]. However, some of these projects had to be constructed in areas with complex geological conditions and steep terrain due to the restriction of topographic conditions. Various complex slope problems are inevitable during engineering construction [3; 4; 5]. Meanwhile, natural slopes may lose stability due to artificial construction disturbances, which cause huge economic losses and major casualties [6; 7; 8]. Therefore, distinguishing the deformation failure mode of slopes and studying their stability for the support design of slope engineering have great engineering significance in ensuring construction safety [9; 10; 11]. The stability analysis of slopes has always been important in geotechnical engineering. Many scholars have conducted research on the deformation damage mode and stability of slopes [12; 13]. [PERSON] et al. [14] proposed that a connected plastic zone from the foot to the top of the slope was a sign of slope instability. [PERSON] et al. [15] analyzed the stability of a slope and took an abrupt change in a slope's vertical displacement as the criterion of slope instability. At present, the stability analysis of slopes mainly includes the limit equilibrium method, probability analysis method, fuzzy mathematical, artificial intelligence, and finite element reduction methods, as shown in Table 1. [PERSON] et al. [16; 17; 18] classified Q-slope based on slope angle, studied the influence of Q-slope angle on slope stability, and successfully evaluated slope stability based on the susceptibility of an artificial neural network. However, the reliability, fuzzy mathematics, and artificial intelligence methods are relatively poor in interpretation and rely on the experience of engineers for efficiency [19; 20; 21]. According to the static equilibrium condition of a three-dimensional sliding body, [PERSON] et al. [22] deduced the limit equilibrium solution of three-dimensional slope stability on the basis of the calculation model of the sliding surface's normal stress and the Mohr-Coulomb strength criterion. However, the existing research shows a significant deviation in slope stability study using the limit equilibrium method and illustrates that the landslide risk is often overestimated [23; 24]. [PERSON] et al. [25] analyzed the influence of the spatial variability of soil shear strength parameters on slope stability on the basis of the finite element limit analysis method and the strength reduction method of the generalized variational principle and compared it with those of three typical limit equilibrium meth  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **Advantage** & **Disadvantage** \\ \hline \multirow{4}{*}{Limit equilibrium method} & The physical meaning of parameters and structures is very clear, the formula is simple and easy to understand intuitively. & Without considering the relationship between material stress and material strain, the obtained safety factor is only the average safety degree on the assumed sliding surface. \\ \hline \multirow{4}{*}{Probability analysis method} & The reliability analysis method can objectively and quantitatively reflect the safety of a slope to a certain extent. & The probability model of each factor and its numerical characteristics cannot be reasonably selected, and the calculation process is relatively complex. \\ \hline \multirow{4}{*}{Fuzzy mathematical method} & It is convenient to obtain objective and fair evaluation conclusions with strong uncertain information processing ability. & There is strong subjectivity when determining attribute weight. The problem of information overlap between evaluation reference levels cannot be solved. The calculation process is complicated. \\ \hline \multirow{4}{*}{Neural network method} & It has obvious advantages in solving nonlinear problems and excellent performance in modeling nonlinear multivariate problems.