Symbolic Regression Model for Predicting Compression Strength of Prismatic Masonry Columns Confined by FRP
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- @Article{alotaibi:2023:Buildings,
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author = "Khalid Saqer Alotaibi and A. B. M. Saiful Islam",
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title = "Symbolic Regression Model for Predicting Compression
Strength of Prismatic Masonry Columns Confined by
{FRP}",
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journal = "Buildings",
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year = "2023",
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volume = "13",
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number = "2",
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pages = "Article No. 509",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "2075-5309",
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URL = "https://www.mdpi.com/2075-5309/13/2/509",
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DOI = "doi:10.3390/buildings13020509",
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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.",
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notes = "also known as \cite{buildings13020509}",
- }
Genetic Programming entries for
Khalid Saqer Alotaibi
A B M Saiful Islam
Citations