FAI: Fast, accurate, and intelligent approach and prediction tool for flexural capacity of FRP-RC beams based on super-learner machine learning model
<p dir="ltr">Fiber-reinforced polymer (FRP) composites have recently been considered in the field of structural engineering as one of the best alternatives to conventional steel reinforcement due to their high tensile strength, lightweight, cost-effectiveness, and superior corrosion...
Saved in:
| Main Author: | Tadesse G. Wakjira (14779165) (author) |
|---|---|
| Other Authors: | Abdelrahman Abushanab (17268940) (author), Usama Ebead (14779168) (author), Wael Alnahhal (14152461) (author) |
| Published: |
2022
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Flexural Performance of RC Beams with Hybrid Combination of Conventional FRP and PET Laminates
by: Al Rashed, Ahmed Yousef
Published: (2023) -
Finite Element Simulation of FRP-Strengthened Thin RC Slabs
by: Assad, Maha
Published: (2022) -
Performance of RC beams externally strengthened with hybrid CFRP and PET-FRP laminates
by: Mhannaa, Haya H.
Published: (2022) -
Machine learning-aided prediction of COD removal in the electrocoagulation process using a super learner model
by: Mhd Taisir Albaba (20601071)
Published: (2025) -
Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
by: Tadesse G. Wakjira (14779165)
Published: (2022)