基于ν-SVR和改进PSO算法的反分析方法及应用

A new back-analysis method based on ν-SVR and improved PSO algorithm and its application

岩土工程反分析面临着多元化、复杂化和精确化的挑战,反分析方法要求能在少而精的正分析基础上结合监测数据快速反馈出数值计算参数。充分发挥支持向量回归机ν-SVR和改进的变邻域PSO算法的优势,建立起岩土工程反分析的流程和方法。同时,将其应用于锦屏左岸边坡的反分析问题,选择稳定问题非常突出的Ⅱ1-Ⅱ1剖面作为分析对象,根据监测资料反馈设计关键岩体的力学参数,并与监测数据比对,反演成果合理准确,进一步验证了该方法的的正确性和有效性。

Challenged by diversity,complexity and precision in geotechnical engineering practices,back-analysis methods are required to quickly obtain feedback parameters for numerical simulations on the basis of monitoring data with fewer but more elaborate forward numerical simulations.Thanks to the specialties of support vector regression machine(ν-SVR) and improved partical swarm optimization(PSO) algorithm with variable neighborhood,a method and process for geotechnical back-analysis is set up.And to prove the correctness and validity of the proposed method,a case study of back-analysis of the left slope of Jinping-Ⅰ hydropower station is carried out.According to the monitoring data of troublesome profile Ⅱ1-Ⅱ1 in project site,critical deformation parameters for forward numerical simulations are fed back with the proposed method,and the results of further simulation with the feedback parameters match the monitoring data fairly well.