New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach
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- @Article{javed:2020:Crystals,
-
author = "Muhammad Faisal Javed and Furqan Farooq and
Shazim Ali Memon and Arslan Akbar and Mohsin Ali Khan and
Fahid Aslam and Rayed Alyousef and Hisham Alabduljabbar and
Sardar Kashif Ur Rehman",
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title = "New Prediction Model for the Ultimate Axial Capacity
of {Concrete-Filled} Steel Tubes: An Evolutionary
Approach",
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journal = "Crystals",
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year = "2020",
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volume = "10",
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number = "9",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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ISSN = "2073-4352",
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URL = "https://www.mdpi.com/2073-4352/10/9/741",
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DOI = "doi:10.3390/cryst10090741",
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abstract = "The complication linked with the prediction of the
ultimate capacity of concrete-filled steel tubes (CFST)
short circular columns reveals a need for conducting an
in-depth structural behavioural analyses of this member
subjected to axial-load only. The distinguishing
feature of gene expression programming (GEP) has been
used for establishing a prediction model for the axial
behaviour of long CFST. The proposed equation
correlates the ultimate axial capacity of long circular
CFST with depth, thickness, yield strength of steel,
the compressive strength of concrete and the length of
the CFST, without need for conducting any expensive and
laborious experiments. A comprehensive CFST short
circular column under an axial load was obtained from
extensive literature to build the proposed models, and
subsequently implemented for verification purposes.
This model consists of extensive database literature
and is comprised of 227 data samples. External
validations were carried out using several statistical
criteria recommended by researchers. The developed GEP
model demonstrated superior performance to the
available design methods for AS5100.6, EC4, AISC, BS,
DBJ and AIJ design codes. The proposed design equations
can be reliably used for pre-design purposes—or
may be used as a fast check for deterministic
solutions.",
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notes = "also known as \cite{cryst10090741}",
- }
Genetic Programming entries for
Muhammad Faisal Javed
Furqan Farooq
Shazim Ali Memon
Arslan Akbar
Mohsin Ali Khan
Fahid Aslam
Rayed Alyousef
Hisham Alabduljabbar
Sardar Kashif Ur Rehman
Citations