Research on Slope Stability Prediction Model of Soil-Rock Mixture Based on Integrated Learning Algorithm
That the significant heterogeneity of soil-rock mixture make the stability of soil-rock mixture slope is dif-ficult to predict.Therefore,based on 49 slope samples of soil-rock mixture,four data characteristics of rock con-tent,base overburden inclination,slope height and slope angle were selected as input parameters.The slope stability coefficient was prediction object.The prediction results of each base learner were combined by three integrated learning algorithms of Boosting,Bagging and Stacking and input into the linear regression model to construct a slope stability prediction model.The prediction results of the three algorithm models before and after optimization were compared and analyzed.The results show that the prediction accuracy of the Boosting algorithm model is relatively the highest;After the fruit fly optimization algorithm,the prediction accuracy of the three algorithm models have been significantly improved,while the Boosting algorithm model still has the highest prediction accuracy,and the R2 value of FOA-Boosting is close to 1.
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