›› 2006, Vol. 27 ›› Issue (4): 591-593.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Forecasting evolution of tunnel surrounding rock displacement by ? -SVR

CHEN Qiu-nan1, 2, ZHANG Yong-xing2, ZHAO Ming-hua3, LIU Xin-rong2   

  1. 1. School of Civil Engineering, Hunan University of Science & Technology, Xiangtan 411201, China; 2. College of Civil Engineering, Chongqing University, Chongqing 400045, China; 3. College of Civil Engineering, Hunan University, Changsha 410082, China
  • Received:2004-08-04 Online:2006-04-10 Published:2013-11-05

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Abstract: Because the prediction accuracy of gray theory, GA and ANN algorithm is insufficiency for tunnel rock surrounding stability, the method of ?-support vector machines was applied to researching of evolution law for tunnel rock surrounding displacement; and in order to enhance the learning efficiency of ?- support vector machines and the capability of forecasting, the accelerated hybrid genetic algorithm (GA) is used for optimizing parameters of ?-support vector machines. Comparison the forecasting results of gray theory, GA and ANN and monitoring results for tunnel rock surrounding displacement, the results show the learning efficiency and prediction accuracy of ?-support vector machines is superior to gray theory, GA and ANN obviously.

Key words: tunnel engineering, ?-support vector machines, surrounding rock displacement, evolution law

CLC Number: 

  • TU 45
  • 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.
  • 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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