Back analysis of displacement based on support vector machine and continuous tabu search

A new intelligent displacement back analysis was proposed based on support vector machine (SVM) and continuous tabu search (CTS). On the one hand, based on the study samples consisting of the measuring point´ displacements and rock and soil mechanics parameters of positive analysis, the model used SVM to build the nonlinear mapping relationship between them. On the other hand, the model used the global optimization performance of CTS to search the optimal rock and soil mechanics parameters in the global space. The nonlinear mapping relationship built by SVM can fit and forecast the measuring point´ displacements under different parameters with high accuracy, avoiding the complex numerical calculation. Continuous tabu search can prevent object function from trapping in local optimum and improve precision of back analysis. The model was applied to calculate the elastic modulus of the permanent navigation lock high slope of Three Gorges Project on the basis of the measured displacements and the calculated elastic modulus were used to compute displacements of the monitoring points. Calculated values were in good agreement with the measured values, which indicated that the model can be well applied to the displacement back analysis in geotechnical engineering.