The adoption of deep neural network (DNN) to the prediction of soil liquefaction based on shear wave velocity

• Published in: Bulletin of engineering geology and the environment Vol. 80; no. 6; pp. 5053 - 5060
• Main Authors: Zhang, Yonggang, Xie, Yuanlun, Zhang, Yan, Qiu, Junbo, Wu, Sunxin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021
• Subjects: Earth and Environmental Science; Earth Sciences; Foundations; Geoecology/Natural Processes; Geoengineering; Geotechnical Engineering & Applied Earth Sciences; Hydraulics; Nature Conservation; Original Paper; Standard penetration test; Deep neural network; Soil liquefaction; Shear wave velocity; Prediction model

Soil liquefaction has been accepted as one of the factors causing natural disasters and engineering failures in the seismic. The mathematic prediction model for soil liquefaction is widely accepted, and the standard penetration (SPT) and cone penetration test (CPT) prediction model using the machine...