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...
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 |
Similar Items
-
Experimental Study on the Seismic Behavior of Squat SRC Shear Walls with High Axial Load Ratio
by: Lei Zhang, et al.
Published: (2022-08-01) -
Calculation of the shear strength of reinforced and prestressed concrete beams by the shear failure theory /
by: 210203 Walther, Rene
Published: (1964) -
Study on the Shear Capacity of an SRC-RC Transfer Column
by: Wei Huang, et al.
Published: (2018-09-01) -
Optimum design of SRC composite beams
by: Zheng Shan-Suo, et al.
Published: (2008-01-01) -
Shear strength of wood beams /
by: 459729 Keenan, F. J.