Surface Settlement Prediction of Rectangular Pipe-Jacking Tunnel Based on the Machine-Learning Algorithm

Author:

Hu Da1ORCID,Hu Yongjia2,Yi Shun2,Liang Xiaoqiang3,Li Yongsuo4,Yang Xian3

Affiliation:

1. Associate Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China; Hunan Provincial Key Laboratory of Key Technology on Hydropower Development, No. 16, Xiangzhang East Rd., Changsha 410014, China (corresponding author). ORCID: .

2. Master’s Candidate, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China.

3. Lecturer, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China.

4. Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference39 articles.

1. Deep learning neural network model for tunnel ground surface settlement prediction based on sensor data;Cao Y.;Math. Probl. Eng.,2021

2. Prediction of shield tunneling-induced ground settlement using machine learning techniques

3. A numerical investigation of the impact of shield machine’s operation parameters on the settlements above twin stacked tunnels—A case study of Ho Chi Minh urban railway Line 1;Do Ngoc A.;Vietnam J. Earth Sci.,2021

4. Prediction Model of Shield Performance During Tunneling via Incorporating Improved Particle Swarm Optimization Into ANFIS

5. Numerical and artificial neural network analyses of ground surface settlement of tunnel in saturated soil

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