Developing Hybrid Machine Learning Models for Estimating the Unconfined Compressive Strength of Jet Grouting Composite: A Comparative Study
Coal-grout composites were fabricated in this study using the jet grouting (JG) technique to enhance coal mass in underground conditions. To evaluate the mechanical properties of the created coal-grout composite, its unconfined compressive strength (UCS) needed to be tested. A mathematical model is...
Main Authors: | Yuantian Sun, Guichen Li, Junfei Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-02-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/5/1612 |
Similar Items
-
Investigation on jet grouting support strategy for controlling time‐dependent deformation in the roadway
by: Yuantian Sun, et al.
Published: (2020-06-01) -
Assessment of compressive strength of jet grouting by machine learning
by: Esteban Díaz, et al.
Published: (2024-01-01) -
Numerical Simulations of Settlement of Jet Grouting Columns
by: Juzwa Anna, et al.
Published: (2016-03-01) -
Discussion on the Influence of Various Technological Parameters on Jet Grouting Columns Geometry
by: Bzówka Joanna, et al.
Published: (2015-06-01) -
Experimental and numerical investigation on a novel support system for controlling roadway deformation in underground coal mines
by: Yuantian Sun, et al.
Published: (2020-02-01)