A Gene Expression Programming Environment for Fatigue Modeling of Composite Materials
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{conf/setn/AntoniouGTVL10,
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title = "A Gene Expression Programming Environment for Fatigue
Modeling of Composite Materials",
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author = "Maria A. Antoniou and Efstratios F. Georgopoulos and
Konstantinos A. Theofilatos and
Anastasios P. Vassilopoulos and Spiridon D. Likothanassis",
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booktitle = "6th Hellenic Conference on Artificial Intelligence:
Theories, Models and Applications (SETN 2010)",
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year = "2010",
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volume = "6040",
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editor = "Stasinos Konstantopoulos and Stavros J. Perantonis and
Vangelis Karkaletsis and Constantine D. Spyropoulos and
George A. Vouros",
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pages = "297--302",
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series = "Lecture Notes in Computer Science",
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address = "Athens, Greece",
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month = may # " 4-7",
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publisher = "Springer",
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isbn13 = "978-3-642-12841-7",
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keywords = "genetic algorithms, genetic programming",
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bibdate = "2010-05-11",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/setn/setn2010.html#AntoniouGTVL10",
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DOI = "doi:10.1007/978-3-642-12842-4",
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abstract = "In the current paper is presented the application of a
Gene Expression Programming Environment in modeling the
fatigue behavior of composite materials. The
environment was developed using the JAVA programming
language, and is an implementation of a variation of
Gene Expression Programming. Gene Expression
Programming (GEP) is a new evolutionary algorithm that
evolves computer programs (they can take many forms:
mathematical expressions, neural networks, decision
trees, polynomial constructs, logical expressions, and
so on). The computer programs of GEP, irrespective of
their complexity, are all encoded in linear
chromosomes. Then the linear chromosomes are expressed
or translated into expression trees (branched
structures). Thus, in GEP, the genotype (the linear
chromosomes) and the phenotype (the expression trees)
are different entities (both structurally and
functionally). This is the main difference between GEP
and classical tree based Genetic Programming
techniques. In order to evaluate the performance of the
presented environment, we tested it in fatigue modeling
of composite materials.",
- }
Genetic Programming entries for
Maria A Antoniou
Efstratios F Georgopoulos
Konstantinos A Theofilatos
Anastasios P Vassilopoulos
Spiridon D Likothanassis
Citations