Displacement Prediction of Tunnel Surrounding Rock: A Comparison of Support Vector Machine and Artificial Neural Network

作者：Wu, Qingdong; Yan, Bo; Zhang, Chao; Wang, Lu; Ning, Guobao^*; Yu, B.

来源：Mathematical Problems in Engineering, 2014, 2014: 351496.

DOI：10.1155/2014/351496

• STEP-AHEAD PREDICTION
• HYBRID MODEL
• OPTIMIZATION

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.

• 出版日期2014
• 单位同济大学; 北京交通大学; 大连海事大学