›› 2003, Vol. 24 ›› Issue (4): 631-633.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Forecasting evolution of slope deformation by genetic-support vector machine

ZHAO Hong-bo, FENG Xia-ting, LI Shao-jun, YIN Shun-de   

  1. Key Laboratory of Rock and soil Mechanics, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
  • Received:2002-06-14 Online:2003-08-11 Published:2014-08-19

Abstract: The Method of genetic-support vector machine was applied to forecast the deformation of slope.It is showen that this method can escape from the blindness which is the common phenomenon in man-made choice of parameters of support vector machine.It enhances the learning efficiency of the support vector machine and the capability of forecasting.Through comparison between the forecasting and monitoring deformations, it can help the engineer to modify the plan and keep the stabilization of slope.The engineering case analysis indicates that there is an extensive prospect for the genetic-support vector machine.

Key words: support vector machine, genetic algorithm, slope, forcast

CLC Number: 

  • P 642. 22 O242
  • Please send e-mail to pingzhou3@126.com if you would like to read full paper in English for free. Parts of our published papers have English translations.
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