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Predicting GFRP-Confined Concrete Strength by sahmir khan is a document available to read on EtoBox.

This study presents a metaheuristics-guided machine learning model for predicting the compressive strength of glass fiber-reinforced polymer confined concrete columns, utilizing a comprehensive database of 319 experimental results. The model, particularly the Stochastic Paint Optimizer-ANN variant, achieved high accuracy with a coefficient of determination of 0.9630, while critical factors influencing compressive strength were identified. This innovative approach aims to streamline the prediction process, r

Author
sahmir khan
Language
EN