Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading
The residual shear strength of liquefied soil is critical to estimating the displacement of lateral spreading. In the paper, an Artificial Neural Network model was trained to predict the residual shear strength ratio based on the case histories of lateral spreading. High-quality case histories were...
Main Authors: | Yanxin Yang, Bai Yang, Chunhui Su, Jianlin Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/8886781 |
Similar Items
-
Evaluating Lateral Spreading Using Newmark Method Based on Liquefaction Triggering
by: Yanxin Yang, et al.
Published: (2020-01-01) -
A Hybrid Approach Calculating Lateral Spreading Induced by Seismic Liquefaction
by: Yanxin Yang, et al.
Published: (2020-01-01) -
Prediction of Residual Strength of Heated Concrete Based on Artificial Neural Networks
by: Chun-Chieh Yang, et al. -
Unsaturated soil stiffness and post-liquefaction shear strength
by: Cho, Gye Chun
Published: (2008) -
Model Tests and Numerical Simulations of Liquefaction and Lateral Spreading LEAP-UCD-2017
Published: (2020)