A virtual calibration chamber for cone penetration test based on deep-learning approaches

A virtual calibration chamber for cone penetration test based on deep-learning approaches

The interpretation of the cone penetration test (CPT) still relies largely on empirical correlations that have been predominantly developed in resource-intensive and time-consuming calibration chambers. This paper presents a CPT virtual calibration chamber using deep learning (DL) approaches, which...

Full description

Bibliographic Details
Main Authors: Mingpeng Liu, Enci Sun, Ningning Zhang, Fengwen Lai, Raul Fuentes
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Journal of Rock Mechanics and Geotechnical Engineering
Subjects:
Cone penetration test (CPT)
Virtual calibration chamber
Bayesian optimization (BO)
Multilayer perceptron (MLP)
Long short-term memory (LSTM) network
Online Access:http://www.sciencedirect.com/science/article/pii/S1674775524004761

Internet

http://www.sciencedirect.com/science/article/pii/S1674775524004761

Similar Items