Local Crossover: A New Genetic Operator for Grammatical Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.8506
- @Article{tsoulos:2024:AlgorithmsXO,
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author = "Ioannis G. Tsoulos and Vasileios Charilogis and
Dimitrios Tsalikakis",
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title = "Local Crossover: A New Genetic Operator for
Grammatical Evolution",
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journal = "Algorithms",
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year = "2024",
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volume = "17",
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number = "10",
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pages = "Article No. 461",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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ISSN = "1999-4893",
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URL = "
https://www.mdpi.com/1999-4893/17/10/461",
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DOI = "
doi:10.3390/a17100461",
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abstract = "The presented work outlines a new genetic crossover
operator, which can be used to solve problems by the
Grammatical Evolution technique. This new operator
intensively applies the one-point crossover procedure
to randomly selected chromosomes with the aim of
drastically reducing their fitness value. The new
operator is applied to chromosomes selected randomly
from the genetic population. This new operator was
applied to two techniques from the recent literature
that exploit Grammatical Evolution: artificial neural
network construction and rule construction. In both
case studies, an extensive set of classification
problems and data-fitting problems were incorporated to
estimate the effectiveness of the proposed genetic
operator. The proposed operator significantly reduced
both the classification error on the classification
datasets and the feature learning error on the fitting
datasets compared to other machine learning techniques
and also to the original models before applying the new
operator.",
-
notes = "also known as \cite{a17100461}",
- }
Genetic Programming entries for
Ioannis G Tsoulos
Vasileios Charilogis
Dimitrios Tsalikakis
Citations