Optimization of existing equations using a new genetic programming algorithm: application to the shear strength of reinforced concrete beams
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Optimization of existing equations using a new genetic programming algorithm: application to the shear strength of reinforced concrete beamsDate
2012-03-13Citation
Pérez JL, Cladera A, Rabuñal JR, Martínez-Abella F. Optimization of existing equations using a new genetic programming algorithm: application to the shear strength of reinforced concrete beams. Adv Eng Softw. 2012;50:82-96
Abstract
[Abstract] A method based on Genetic Programming (GP) to improve previously known empirical equations is presented. From a set of experimental data, the GP may improve the adjustment of such formulas through the symbolic regression technique. Through a set of restrictions, and the indication of the terms of the expression to be improved, GP creates new individuals. The methodology allows us to study the need of including new variables in the expression. The proposed method is applied to the shear strength of concrete beams. The results show a marked improvement using this methodology in relation to the classic GP and international code procedures.
Keywords
Artificial intelligence
Genetic programming
Structural engineering
Concrete
Shear strength
Regression analysis
Genetic programming
Structural engineering
Concrete
Shear strength
Regression analysis
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Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
0965-9978