首页|New Machine Learning Study Findings Recently Were Reported by Researchers at Beijing University of Technology (Elastic Analytical Method With Machine Learning for Predicting the Stratum Displacement Field Induced By Shallow Tunneling)

New Machine Learning Study Findings Recently Were Reported by Researchers at Beijing University of Technology (Elastic Analytical Method With Machine Learning for Predicting the Stratum Displacement Field Induced By Shallow Tunneling)

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New research on Machine Learning is the subject of a report. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Support vector regression (SVR) with sparrow search algorithm (SSA) is developed as the machine learning (ML) model to predict maximum surface settlement smax caused by tunneling. A novel method for calibrating boundary conditions of analytical solution is proposed, where the maximum surface settlement derived by the analytical method is equal to smax predicted by SSA-SVR method.” Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), Beijing Municipal Commission of Education. Our news journalists obtained a quote from the research from the Beijing University of Technology, “The elastic analytical solution for stratum displacement of a shallow tunnel is presented by the complex variable method, when the calibrated nonuniform displacement function is applied as the tunnel displacement boundary condition. The proposed analytical solution-machine learning (AM) method can predict the stratum displacement field prior to the tunnel excavation. Seventythree tunnel engineering cases are employed to verify the rationality of the proposed SSA-SVR method in predicting smax. The value of R2 in the training and test process is 0.894 and 0.877, respectively. Taking Heathrow Express Trial Tunnel as an example, the potential of the proposed AM method in predicting stratum displacement is presented where the influence of cohesion strength, internal friction angle, Young’s elastic modulus of stratum, tunnel radius and depth are considered.”

BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningBeijing University of Technology

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.7)
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