Universal Models for Heavy-Ion Fusion Cross Section Above-Barrier
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Lombardo:2023:EPJ,
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author = "Ivano Lombardo and Daniele Dell'Aquila and
Brunilde Gnoffo and Luigi Redigolo and Francesco Porto and
Marco Russo",
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title = "Universal Models for Heavy-Ion Fusion Cross Section
Above-Barrier",
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journal = "EPJ Web of Conferences",
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year = "2023",
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volume = "290",
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pages = "Article Number: 02017",
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keywords = "genetic algorithms, genetic programming, BP",
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ISSN = "2100-014X",
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URL = "https://www.epj-conferences.org/articles/epjconf/pdf/2023/16/epjconf_eunpc2023_02017.pdf",
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DOI = "doi:10.1051/epjconf/202329002017",
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size = "4 pages",
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abstract = "The paper discusses a recent re-investigation of a
large body of heavy-ion fusion cross section data with
the aim of deriving a simple phenomenological model
able to describe data from the Coulomb barrier up to
the onset of nuclear multifragmentation. To this end,
we adopted two complementary approaches: a first
universal phenomenological model was derived exploiting
a novel artificial intelligence tool for the formal
modeling of large datasets. This tool is capable of
advanced feature selection and is ideal to drive the
discovery process even using traditional methods. A
second phenomenological model was derived using a
sum-of-difference approach and achieved an
unprecedented accuracy in describing above-barrier
fusion excitation functions data. Future perspectives
and opportunities arising from the present models are
also discussed in the text.",
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notes = "Section P2 Nuclear Structure, Spectroscopy and
Dynamics",
- }
Genetic Programming entries for
Ivano Lombardo
Daniele Dell'Aquila
Brunilde Gnoffo
Luigi Redigolo
Francesco Porto
Marco Russo
Citations