Paper Title:
Applying Support Vector Machines to Predict Tunnel Surrounding Rock Displacement
  Abstract

Displacement prediction of tunnel surrounding rock plays a significant role for safety estimation during tunnel construction. This paper presents an approach to use support vector machines (SVM) to predict tunnel surrounding rock displacement. A stepwise search is also introduced to optimize the parameters in SVM. The data of Fangtianchong tunnel is use to evaluate the proposed model. The comparison between artificial neural network (ANN) and SVM shows that SVM has a high-accuracy prediction than ANN. Results also show SVM seems to be a powerful tool for tunnel surrounding rock displacement prediction.

  Info
Periodical
Edited by
Honghua Tan
Pages
1717-1721
DOI
10.4028/www.scientific.net/AMM.29-32.1717
Citation
B. Z. Yao, C. Y. Yang, B. Yu, F. F. Jia, B. Yu, "Applying Support Vector Machines to Predict Tunnel Surrounding Rock Displacement", Applied Mechanics and Materials, Vols. 29-32, pp. 1717-1721, 2010
Online since
August 2010
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Price
$32.00
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