A Multi-Objective Evolutionary Framework for Formulation of Nonlinear Structural Systems
Created by W.Langdon from
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- @Article{Gandomi:II,
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author = "Amir H Gandomi and David Roke",
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journal = "IEEE Transactions on Industrial Informatics",
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title = "A Multi-Objective Evolutionary Framework for
Formulation of Nonlinear Structural Systems",
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year = "2022",
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volume = "18",
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number = "9",
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pages = "5795--5803",
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keywords = "genetic algorithms, genetic programming, Evolutionary
Computation, Feature Selection, Formulation,
Self-centering concentrically braced frame,
Multi-objective",
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ISSN = "1941-0050",
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URL = "https://www.human-competitive.org/sites/default/files/entryform.txt",
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URL = "https://www.human-competitive.org/sites/default/files/tii3126702.pdf",
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DOI = "doi:10.1109/TII.2021.3126702",
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size = "9 pages",
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abstract = "an evolutionary framework is proposed for seismic
response formulation of self-centering concentrically
braced frame (SC-CBF) systems. A total of 75 different
SC-CBF systems were designed, and their responses were
recorded under 170 earthquake records. To select the
most important earthquake intensity measures, an
evolutionary feature selection strategy is introduced,
which tries to find the highest correlation. For the
formulation of the SC-CBF response, a hybrid
multi-objective genetic programming and regression
analysis is implemented, considering both model
accuracy and model complexity as objectives. In the
hybrid approach, regression tries to connect multiple
genes. Non-dominated models are presented, and the best
model is selected based on the practical approach
proposed here. The best model is compared with four
other genetic programming models. The results show that
the evolutionary procedure is highly effective for
designing the SC-CBF system using a simple and accurate
model for such a complex system.",
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notes = "Entered 2022 HUMIES
Also known as \cite{9609645}
University of Technology Sydney, Australia",
- }
Genetic Programming entries for
A H Gandomi
David Roke
Citations