Research on intelligent elasto-plastic displacement back analysis by using the improved GA-SVR algorithm in long and large tunnel
One improved SVR algorithm was introduced into the field of elasto-plastic displacement back analysis in this paper. The strong nonlinear and uncertain relation between calculation parameters of rock mass and displacement of surrounding rock was described by the improved SVR algorithm. In order to find the optimal parameters of this improved SVR model during samples training course, the Genetic Algorithm (GA) was combined with it to form the improved GA-SVR algorithm. After the optimal non-linear mapping between the elasto-plastic mechanical parameters and displacement had been established, GA was used to identify these mechanical parameters within their search interval. By dint of MATLAB toolbox, GA also was integrate with BP neural network to form the GABP algorithm. Compared the back analysis results of the same elasto-plastic model parameters in BAOZHEN long and large railway tunnel by the two different algorithms, it can be concluded that the improved GA-SVR algorithm can obtain a more high inversion precision and calculation efficiency than that of GA-BP algorithm, so the improved GA-SVR can be applied in similar geotechnical engineering.
K.Y.LIU B.G.LIU C.S.QIAO
School of Civil Engineering,Beijing Jiaotong University, Beijing
国际会议
香港
英文
1-5
2009-05-19（万方平台首次上网日期，不代表论文的发表时间）