Predictions of Deep Excavation Responses Considering Model Uncertainty: Integrating BiLSTM Neural Networks with Bayesian Updating-Reference-Cited by-同舟云学术

Predictions of Deep Excavation Responses Considering Model Uncertainty: Integrating BiLSTM Neural Networks with Bayesian Updating

Published:2022-01 Issue:1 Volume:22 Page:
ISSN:1532-3641
Container-title:International Journal of Geomechanics
language:en
Short-container-title:Int. J. Geomech.

Author:

Tao Yuanqin¹,Sun Honglei²,Cai Yuanqiang³

Affiliation:

1. Ph.D. Candidate, Research Center of Coastal and Urban Geotechnical Engineering, College of Civil Engineering and Architecture, Zhejiang Univ., Hangzhou 310058, P.R. China.

2. Professor, Institute of Geotechnical Engineering, College of Civil Engineering, Zhejiang Univ. of Technology, Hangzhou 310000, P.R. China (corresponding author).

3. Professor, Research Center of Coastal and Urban Geotechnical Engineering, College of Civil Engineering and Architecture, Zhejiang Univ., Hangzhou 310058, P.R. China; Professor, Institute of Geotechnical Engineering, College of Civil Engineering, Zhejiang Univ. of Technology, Hangzhou 310000, P.R. China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Soil Science

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29GM.1943-5622.0002245

Reference47 articles.

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4. Inference from Iterative Simulation Using Multiple Sequences

5. A simple estimation model for 3D braced excavation wall deflection

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