Applying Support Vector Machines to Predict Tunnel Surrounding Rock Displacement

Abstract:

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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 et al., "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:

$35.00

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