Adapting the Parameters of RBF Networks Using Grammatical Evolution
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- @Article{tsoulos:2023:AI,
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author = "Ioannis G. Tsoulos and Alexandros Tzallas and
Evangelos Karvounis",
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title = "Adapting the Parameters of {RBF} Networks Using
Grammatical Evolution",
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journal = "AI",
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year = "2023",
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volume = "4",
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number = "4",
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pages = "1059--1078",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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ISSN = "2673-2688",
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URL = "https://www.mdpi.com/2673-2688/4/4/54",
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DOI = "doi:10.3390/ai4040054",
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abstract = "Radial basis function networks are widely used in a
multitude of applications in various scientific areas
in both classification and data fitting problems. These
networks deal with the above problems by adjusting
their parameters through various optimisation
techniques. However, an important issue to address is
the need to locate a satisfactory interval for the
parameters of a network before adjusting these
parameters. This paper proposes a two-stage method. In
the first stage, via the incorporation of grammatical
evolution, rules are generated to create the optimal
value interval of the network parameters. During the
second stage of the technique, the mentioned parameters
are fine-tuned with a genetic algorithm. The current
work was tested on a number of datasets from the recent
literature and found to reduce the classification or
data fitting error by over 40percent on most datasets.
In addition, the proposed method appears in the
experiments to be robust, as the fluctuation of the
number of network parameters does not significantly
affect its performance.",
-
notes = "also known as \cite{ai4040054}",
- }
Genetic Programming entries for
Ioannis G Tsoulos
Alexandros T Tzallas
Evangelos Karvounis
Citations