Predicting the Compressive Strength of Glass Fiber-Reinforced Polymer Confined-Concrete Elements Using Metaheuristics-Guided Machine Learning

Abstract Glass fiber-reinforced polymers (GFRP) are widely applied to enhance the strength of concrete columns due to their lightweight and high-strength characteristics. This study presents the development of a metaheuristics-guided machine learning (ML) model for predicting the compressive strengt...

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Autores principales:	Nima Khodadadi, Emad Golafshani, Hossein Roghani, Ali Behnood, El-Sayed M. El-kenawy, Tuan Ngo, Antonio Nanni
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	SpringerOpen 2025-10-01
Colección:	International Journal of Concrete Structures and Materials
Materias:	Metaheuristic algorithms Glass fiber-reinforced polymer Confined-concrete Compressive strength
Acceso en línea:	https://doi.org/10.1186/s40069-025-00841-w
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