岩土力学2009，Vol.30Issue(z2)：540-546,7.
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
邢万波 1周钟 1唐忠敏 1孙钢2
作者信息
- 1. 中国水电顾问集团成都勘测设计研究院,成都,610072
- 2. 四川省水利水电勘测设计研究院,成都,610072
- 折叠
摘要
Abstract
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.关键词
反分析/支持向量回归机(ν-SVR)/PSO算法/锦屏左岸边坡Key words
back-analysis/ support vector regression machine(ν-SVR)/ particle swarm optimization algorithm (PSO)/ left slope of Jinping分类
建筑与水利引用本文复制引用
邢万波,周钟,唐忠敏,孙钢..基于ν-SVR和改进PSO算法的反分析方法及应用[J].岩土力学,2009,30(z2):540-546,7.
