Seismic response prediction method of RC frame structure based on XGBoost model of ensemble learning
In order to realize the rapid prediction of seismic response of reinforced concrete(RC)frame structure,a seismic response prediction method of RC frame structure based on ensemble learning is proposed.Three RC frame structures,namely low-rise,multi-story and small high-rise,were designed as research examples.The ground motion records were selected according to the conditional mean spectrum(CMS),and the sample database was built through elastoplastic time history analysis.The structural response was predicted with the input of ground motion intensity information and structural information,and the feature importance of the model was analyzed.The results show that the established XGBoost model has better generalization performance than the gradient boosting regression tree(GBRT)model,and the relative importance of the average spectral acceleration(AvgSa)in the char-acteristic parameters is the largest.The proposed method provides a reference for quickly predicting the seismic response of RC frame structures and has high application value.
NETL
NSTL
万方数据
维普
