ICCK Transactions on Systems Safety and Reliability | Volume 2, Issue 2: 82-100, 2026 | DOI: 10.62762/TSSR.2026.963232
Abstract
To improve the prediction accuracy of slope stability and prevent slope failure accidents, this study proposes a slope stability prediction model based on an improved pelican optimization algorithm optimized random forest (Improved Pelican Optimization Algorithm optimized Random Forest, IPOA-RF). First, according to 431 slope cases, the slope height, slope angle, unit weight, cohesion, internal friction angle, and pore water pressure ratio were selected as the main predictive features. Second, due to the issue of excessive hyperparameters in the traditional random forest (RF) model, the IPOA algorithm was employed to optimize the RF parameters using an optimal-guidance strategy, mutation op... More >
Graphical Abstract