The safety factor is a crucial quantitative index for evaluating slope ***,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influenc...
详细信息
The safety factor is a crucial quantitative index for evaluating slope ***,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influencing factors,leading to large errors in their ***,a stacking ensemble learning model(stacking-SSAOP)based on multi-layer regression algorithm fusion and optimized by the sparrow search algorithm is proposed for predicting the slope safety *** this method,the density,cohesion,friction angle,slope angle,slope height,and pore pressure ratio are selected as characteristic parameters from the 210 sets of established slope sample *** Forest,Extra Trees,AdaBoost,Bagging,and Support Vector regression are used as the base model(inner loop)to construct the first-level regressionalgorithmlayer,and XGBoost is used as the meta-model(outer loop)to construct the second-level regressionalgorithmlayer and complete the construction of the stacked learning model for improving the model prediction *** sparrow search algorithm is used to optimize the hyperparameters of the above six regression models and correct the over-and underfitting problems of the single regression model to further improve the prediction *** mean square error(MSE)of the predicted and true values and the fitting of the data are compared and *** MSE of the stacking-SSAOP model was found to be smaller than that of the single regression model(MSE=0.03917).Therefore,the former has a higher prediction accuracy and better data *** study innovatively applies the sparrow search algorithm to predict the slope safety factor,showcasing its advantages over traditional ***,our proposed stacking-SSAOP model integrates multiple regressionalgorithms to enhance prediction *** model not only refines the prediction accuracy of the slope safety factor but also offers a fresh approach to handling the intricate
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