Displacement Prediction of Tunnel Surrounding Rock : A Comparison of Support Vector Machine and Artificial Neural Network
Joint Authors
Ning, Guobao
Yu, B.
Wang, Lu
Wu, Qingdong
Yan, Bo
Zhang, Chao
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-23
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Displacement prediction of tunnel surrounding rock plays an important role in safety monitoring and quality control tunnel construction.
In this paper, two methodologies, support vector machines (SVM) and artificial neural network (ANN), are introduced to predict tunnel surrounding rock displacement.
Then the two modes are texted with the data of Fangtianchong tunnel, respectively.
The comparative results show that solutions gained by SVM seem to be more robust with a smaller standard error compared to ANN.
Generally, the comparison between artificial neural network (ANN) and SVM shows that SVM has a higher accuracy prediction than ANN.
Results also show that SVM seems to be a powerful tool for tunnel surrounding rock displacement prediction.
American Psychological Association (APA)
Wu, Qingdong& Yan, Bo& Zhang, Chao& Wang, Lu& Ning, Guobao& Yu, B.. 2014. Displacement Prediction of Tunnel Surrounding Rock : A Comparison of Support Vector Machine and Artificial Neural Network. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-465025
Modern Language Association (MLA)
Wu, Qingdong…[et al.]. Displacement Prediction of Tunnel Surrounding Rock : A Comparison of Support Vector Machine and Artificial Neural Network. Mathematical Problems in Engineering No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-465025
American Medical Association (AMA)
Wu, Qingdong& Yan, Bo& Zhang, Chao& Wang, Lu& Ning, Guobao& Yu, B.. Displacement Prediction of Tunnel Surrounding Rock : A Comparison of Support Vector Machine and Artificial Neural Network. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-465025
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-465025