Seismic fragility analysis of RC box-girder bridges based on symbolic regression method
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- @Article{REZAEI:2022:istruc,
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author = "Hossein Rezaei and Panam Zarfam and
Emadaldin Mohammadi Golafshani and Gholamreza Ghodrati Amiri",
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title = "Seismic fragility analysis of {RC} box-girder bridges
based on symbolic regression method",
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journal = "Structures",
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volume = "38",
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pages = "306--322",
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year = "2022",
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ISSN = "2352-0124",
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DOI = "doi:10.1016/j.istruc.2021.12.058",
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URL = "https://www.sciencedirect.com/science/article/pii/S2352012421011760",
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keywords = "genetic algorithms, genetic programming, Evolutionary
computation, Regression analysis, Fragility curve,
Machine learning, Automatic regression, Multi-span
bridge, Nonlinear time history analysis, Bridges with
Unequal-Height Piers",
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abstract = "The fragility curves are the key tools in seismic risk
assessment within the performance-based earthquake
engineering framework. This study employs the Symbolic
Regression (SR) analysis to develop seismic response
prediction models and the fragility curves for concrete
box-girder bridges. Geometrical, material, ground
motion, and structural uncertainties were taken into
account to improve the reliability of the derived
mathematical models. The responses were recorded as
Engineering Demand Parameters (EDPs) through a
nonlinear time history analysis of the simulated
bridges and used as targets for prediction algorithms.
The parameters of higher significance were then
identified based on the evolutionary correlation
coefficient and adopted as input parameters.
Accordingly, a total of 30 mathematical models were
developed for the five classes of regular and irregular
bridges and six EDPs. The model accuracy and
effectiveness were evaluated based on various criteria.
A method was then proposed to develop fragility curves
based on the resulting prediction models. The results
were suggestive of the effectiveness and accuracy of
the prediction models despite their simplicity.
Further, the resulting fragility curves were consistent
with those obtained by nonlinear time history analysis
and, for different EDPs, the geometrical parameters
were among the highest-correlation parameters after the
seismic intensity measure",
- }
Genetic Programming entries for
Hossein Rezaei
Panam Zarfam
Emadaldin Mohammadi Golafshani
Gholamreza Ghodrati Amiri
Citations