Genetic Programming to Improvement FIB Model - Bond and Anchorage of Reinforcing Steel in Structural Concrete

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{conf/iwann/PerezVRA13,

• author = "Juan Luis Perez and Ismael Vieito and Juan R. Rabunal and Fernando Martinez-Abella",
• title = "Genetic Programming to Improvement {FIB} Model - Bond and Anchorage of Reinforcing Steel in Structural Concrete",
• bibdate = "2013-06-25",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iwann/iwann2013-1.html#PerezVRA13",
• booktitle = "Advances in Computational Intelligence - 12th International Work-Conference on Artificial Neural Networks, {IWANN} 2013, Puerto de la Cruz, Tenerife, Spain, June 12-14, 2013, Proceedings, Part {I}",
• publisher = "Springer",
• year = "2013",
• volume = "7902",
• editor = "Ignacio Rojas and Gonzalo Joya Caparr{\'o}s and Joan Cabestany",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-38678-7",
• pages = "463--470",
• series = "Lecture Notes in Computer Science",
• URL = "http://dx.doi.org/10.1007/978-3-642-38679-4",
• DOI = "doi:10.1007/978-3-642-38679-4_46",
• abstract = "Starting from the FIB database, this work is aimed to analyse the current equations which predict the main datum that can be provided by bond tests: the ultimate bar stress when the failure is reached. Furthermore, Genetic Programming (GP) techniques are also applied in order to enhance the expression of the FIB, which achieves the best adjustment so far, giving rise to the new Model Code 2010. The final result shown is a highly predictive equation. The results are compared with those included in the Model Code and it is showed the influence of the main variables on the phenomenon (concrete strength, yield strength of steel, concrete cover, transverse reinforcement and diameter of the bar).",

}

Genetic Programming entries for Juan Luis Perez Ismael Vieito Juan Ramon Rabunal Dopico Fernando Martinez Abella

Citations