Optimization of existing equations using a new Genetic Programming algorithm: Application to the shear strength of reinforced concrete beams

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Perez201282,

• author = "Juan L. Perez and Antoni Cladera and Juan R. Rabunal and Fernando Martinez-Abella",
• title = "Optimization of existing equations using a new Genetic Programming algorithm: Application to the shear strength of reinforced concrete beams",
• journal = "Advances in Engineering Software",
• volume = "50",
• pages = "82--96",
• year = "2012",
• note = "CIVIL-COMP",
• ISSN = "0965-9978",
• DOI = "doi:10.1016/j.advengsoft.2012.02.008",
• URL = "http://www.sciencedirect.com/science/article/pii/S0965997812000397",
• keywords = "genetic algorithms, genetic programming, Artificial intelligence, Structural engineering, Concrete, Shear strength, Regression analysis",
• 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 formulae 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.",

}

Genetic Programming entries for Juan Luis Perez Antoni Cladera Bohigas Juan Ramon Rabunal Dopico Fernando Martinez Abella

Citations