›› 2009, Vol. 30 ›› Issue (S2): 540-546.

• Numerical Analysis • Previous Articles     Next Articles

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

XING Wan-bo1, ZHOU Zhong1, TANG Zhong-min1, SUN Gang2   

  1. 1.Chengdu Hydroelectric Investigation and Design Institute, China Hydropower Engineering Consulting Group Co., Chengdu, 610072, China; 2.Sichuan Institute of Water Resources and Hydroelectric Exploration Design and Research, Chengdu 610072, China
  • Received:2009-07-25 Online:2009-08-10 Published:2011-06-21

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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.

Key words: back-analysis, support vector regression machine(ν-SVR), particle swarm optimization algorithm (PSO), left slope of Jinping

CLC Number: 

  • TU 443
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