Abstract:On the basis of the traditional support vector regression machine, considering the chaotic properties of observation data, the GA-SVR combination model is built by combining the reconstruction of a phase space of training sample and the advantages of a genetic algorithm in seeking the optimum parameter. After comparing and analyzing the predicted and measured values of slope deformation, we determine that the combination model has higher prediction accuracy.
LIU Xiaosheng,QIN Zhiqiang. GA-SVR Combined Model for Forecasting Landside Displacement: Study on Based on Phase-Space Reconstruction[J]. jgg, 2017, 37(10): 1024-1028.