Flexural buckling load prediction of aluminium alloy columns using soft computing techniques
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Cevik:2008:ESwA2,
-
author = "Abdulkadir Cevik and Nihat Atmaca and
Talha Ekmekyapar and Ibrahim H. Guzelbey",
-
title = "Flexural buckling load prediction of aluminium alloy
columns using soft computing techniques",
-
journal = "Expert Systems with Applications",
-
year = "2009",
-
volume = "36",
-
number = "3, Part 2",
-
pages = "6332--6342",
-
month = apr,
-
keywords = "genetic algorithms, genetic programming, gene
expression programming, Soft computing, Neural
networks, Flexural buckling, Aluminium alloy columns",
-
ISSN = "0957-4174",
-
DOI = "doi:10.1016/j.eswa.2008.08.011",
-
URL = "http://www.sciencedirect.com/science/article/B6V03-4TB6X28-1/2/3f64ccc54bc41be648922dc688ccad4a",
-
size = "11 pages",
-
abstract = "This paper presents the application of soft computing
techniques for strength prediction of heat-treated
extruded aluminium alloy columns failing by flexural
buckling. Neural networks (NN) and genetic programming
(GP) are presented as soft computing techniques used in
the study. Gene-expression programming (GEP) which is
an extension to GP is used. The training and test sets
for soft computing models are obtained from
experimental results available in literature. An
algorithm is also developed for the optimal NN model
selection process. The proposed NN and GEP models are
presented in explicit form to be used in practical
applications. The accuracy of the proposed soft
computing models are compared with existing codes and
are found to be more accurate.",
- }
Genetic Programming entries for
Abdulkadir Cevik
Nihat Atmaca
Talha Ekmekyapar
Ibrahim H Guzelbey
Citations