Symbolic Regression Model for Predicting Compression Strength of Prismatic Masonry Columns Confined by FRP

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@Article{alotaibi:2023:Buildings,

• author = "Khalid Saqer Alotaibi and A. B. M. Saiful Islam",
• title = "Symbolic Regression Model for Predicting Compression Strength of Prismatic Masonry Columns Confined by {FRP}",
• journal = "Buildings",
• year = "2023",
• volume = "13",
• number = "2",
• pages = "Article No. 509",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2075-5309",
• URL = "https://www.mdpi.com/2075-5309/13/2/509",
• DOI = "doi:10.3390/buildings13020509",
• abstract = "The use of Fiber Reinforced Polymer (FRP) materials for the external confinement of existing concrete or masonry members is now an established technical solution. Several studies in the scientific literature show how FRP wrapping can improve the mechanical properties of members. Though there are numerous methods for determining the compressive strength of FRP confined concrete, no generalised formulae are available because of the greater complexity and heterogeneity of FRP-confined masonry. There are two main objectives in this analytical study: (a) proposing an entirely new mathematical expression to estimate the compressive strength of FRP confined masonry columns using symbolic regression model approach which can outperform traditional regression models, and (b) evaluating existing formulas. Over 198 tests of FRP wrapped masonry were compiled in a database and used to train the model. Several formulations from the published literature and international guidelines have been compared against experimental data. It is observed that the proposed symbolic regression model shows excellent performance compared to the existing models. The model is easier, has no restriction and thereby it can be feasibly employed to foresee the behaviour of FRP confined masonry elements. The coefficient of determination for the proposed symbolic regression model is determined as 0.91.",
• notes = "also known as \cite{buildings13020509}",

}

Genetic Programming entries for Khalid Saqer Alotaibi A B M Saiful Islam

Citations