Strength prediction and failure mode classification for SRC shear beams using GA-BP ANN method
For the steel reinforced concrete (SRC) beam, accurately predicting its shear behavior can be quite challenging. Considering the advantages of machine-learning (ML) approaches, the back-propagation (BP) artificial neural network (ANN) method combined with genetic algorithm (GA) was employed to the p...
Saved in:
| Main Authors: | Gangfeng Yao, Bingyi Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
|
| Series: | Case Studies in Construction Materials |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221450952500052X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Impact of Longitudinal and Stirrups Reinforcement Ratio to Shear Strength Capacity of Geopolymer Concrete Beam
by: Y. Tajunnisa, et al.
Published: (2025-03-01) -
Experimental study on the shear strength of partially-encased composite beams with corrugated webs
by: Liusheng Chu, et al.
Published: (2025-07-01) -
Evaluation of the KDS 14 Draft Design Method for Predicting the Shear Strength of Prestressed Concrete Beams
by: Ngoc Hieu Dinh, et al.
Published: (2025-06-01) -
A Review on Mechanism and Influencing Factors of Shear Performance of UHPC Beams
by: Weijie Jin, et al.
Published: (2024-10-01) -
Shear Strengthening and Rehabilitation of Normal Reinforced Concrete Beams: A Review
by: Wrya Abdullah, et al.
Published: (2024-10-01)