Electronics, Год журнала: 2024, Номер 14(1), С. 126 - 126

Опубликована: Дек. 31, 2024

Landslides induced by heavy rainfall are common in southern China and pose significant risks to the safe operation of transmission lines. To ensure reliability line operations, this paper presents a stability prediction model for tower slopes based on Improved Sand Cat Swarm Optimization (ISCSO) algorithm Support Vector Machine (SVM). The ISCSO is enhanced with dynamic reverse learning triangular wandering strategies, which then used optimize kernel penalty parameters SVM, resulting ISCSO-SVM model. In study, typical slope as case database generated through orthogonal experimental design Geo-studio simulations. addition traditional input features, an additional input—transmission catchment area—is incorporated, stable state set predicted output. results demonstrate that achieves highest accuracy, smallest errors across all metrics. Specifically, compared standard MAPE, MAE, RMSE values reduced 70.96%, 71.41%, 57.37%, respectively. effectively predicts slopes, thereby ensuring

Язык: Английский