Deformation evaluation on surrounding rocks of underground caverns based on PSO-LSSVM

Xinhua Xue, Ming Xiao

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


To evaluate the deformation of surrounding rocks of the underground caverns in the Xiangjiaba hydropower station during excavation, a least squares support vector machine (LSSVM) method based on particle swarm optimization (PSO) algorithm is proposed in this study. The PSO algorithm was employed in optimizing the regularization and kernel parameters of the LSSVM. To develop the proposed PSO-LSSVM model, several important factors, such as the geological conditions, location of monitoring instruments, space and time condition before and after measuring, were used as the input parameters, while the displacement of surrounding rocks was the output parameter. Further, the numerical results of the deformations of surrounding rocks were compared with the measured data. The results obtained demonstrate that the proposed PSO-LSSVM model has potential in accurately forecasting the deformation of surrounding rocks of underground caverns subjected to excavation.

Original languageEnglish (US)
Pages (from-to)171-181
Number of pages11
JournalTunnelling and Underground Space Technology
StatePublished - Oct 2017

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Geotechnical Engineering and Engineering Geology


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