Sensitivity analysis of slope stability based on eXtreme gradient boosting and SHapley Additive exPlanations: An...

Slope instability through can cause catastrophic consequences, so slope stability analysis has been a key topic in the field of geotechnical engineering. Traditional analysis methods have shortcomings such as high operational difficulty and time-consuming, for this reason many researchers have carried out slope stability analysis based on AI. However, the current relevant studies only judged the importance of each factor and did not specifically quantify the correlation between factors and slope stability. For this purpose, this paper carried out a sensitivity analysis based on the XGBoost and SHAP. The sensitivity analysis results of SHAP were also validated using GeoStudio software. The selected influence factors included slope height ( $$ ), slope angle ( $$ ), unit weight ( $$ ), cohesion ( $$ ), angle of internal friction ( $$ ) and pore water pressure coefficient ( $$ ). The results showed that $$ and $$ were the most and least important influential parameters, respectively. GeoStudio simulation results showed a negative correlation between $$ , $$ , $$ , $$ and slope stability, while a positive correlation between $$ , $$ and slope stability. However, for real data, SHAP misjudged the correlation between $$ and slope stability. Because current AI lacked common sense knowledge and, leading SHAP unable to effectively explain the real mechanism of slope instability. For this reason, this paper overcame this challenge based on the priori data-driven approach. The method provided more reliable and accurate interpretation of the results than a real sample, especially with limited or low-quality data. In addition, the results of this method showed that the critical values of $$ , $$ , $$ , $$ , and $$ in slope destabilization are 18 Kpa, 28°, 32°, 30 m, and 0.28, respectively. These results were closer to GeoStudio simulations than real samples.