Enhanced Prediction of Bond Strength in Corroded RC Structures Using Advanced Feature Selection and Ensemble Learning Framework
Bond behavior between steel bars and concrete is fundamental to the structural integrity and durability of reinforced concrete. However, corrosion-induced deterioration severely impairs bond performance, highlighting the need for advanced and reliable assessment methods. This paper pioneers an algor...
Saved in:
| Main Authors: | Jin-Yang Gui, Zhao-Hui Lu, Chun-Qing Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Corrosion and Materials Degradation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-5558/6/2/24 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Ensemble Framework for Text Classification
by: Eleni Kamateri, et al.
Published: (2025-01-01) -
Experimental investigation on flexural performance of corroded RC beams with high-strength concrete and steel bars
by: Xiao-Hui Yu, et al.
Published: (2024-12-01) -
ML modeling of ultimate and relative bond strength for corroded rebars based on concrete and steel properties
by: Alireza Hosseinzadeh Kashani, et al.
Published: (2025-07-01) -
Highly efficient stacking ensemble learning model for automated keratoconus screening
by: Zahra J. Muhsin, et al.
Published: (2025-06-01) -
Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning
by: Ray-I Chang, et al.
Published: (2024-07-01)