Publicacións

@article{Pérez2008452,

title = {Applying genetic programming to civil engineering in the improvement of models, codes and norms},

author = {Juan Luis Pérez-Ordóñez and Mónica Miguélez and Juan R. Rabuñal-Dopico and Fernando Martínez-Abella},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449717049&doi=10.1007%2f978-3-540-88309-8_46&partnerID=40&md5=712396029eac63a87210e929fd0c05cf},

doi = {10.1007/978-3-540-88309-8_46},

issn = {03029743},

year  = {2008},

date = {2008-01-01},

urldate = {2008-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {5290 LNAI},

pages = {452-460},

abstract = {This paper presents the use of Evolutionary Computation (EC) techniques, and more specifically the Genetic Programming (GP) technique, to Civil Engineering. This technique is applied here to a phenomenon that models the performance of structural concrete under controlled conditions throughout time. Several modifications were applied to the classic GP algorithm given the temporal nature of the case to be studied; one of these modifications was the incorporation of a new operator for providing the temporal ability for this specific case. The fitness function has been also modified by adding a security coefficient that adjusts the GP-obtained expressions and penalises the expressions that return unstable values. © 2008 Springer-Verlag.},

note = {cited By 7},

keywords = {Artificial intelligence; Calculations; Civil engineering; Creep; Function evaluation; Genetic algorithms; Information analysis; Mathematical operators; Models, Concrete creep; Controlled conditions; Evolutionary computation; Evolutionary computations; Fitness functions; GP algorithm; Information Extraction; Security coefficient; Structural concretes, Genetic programming},

pubstate = {published},

tppubtype = {article}

}