Genetic Programming Based Evolvement of Models of Models
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- @InProceedings{Semenkina:2019:EUROCAST,
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author = "Mariia Semenkina and Bogdan Burlacu and
Michael Affenzeller",
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title = "Genetic Programming Based Evolvement of Models of
Models",
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booktitle = "International Conference on Computer Aided Systems
Theory, EUROCAST 2019",
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year = "2019",
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editor = "Roberto Moreno-Diaz and Franz Pichler and
Alexis Quesada-Arencibia",
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volume = "12013",
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series = "Lecture Notes in Computer Science",
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pages = "387--395",
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address = "Las Palmas de Gran Canaria, Spain",
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month = "17-22 " # feb,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Symbolic
Regression, Models of Models",
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isbn13 = "978-3-030-45092-2",
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DOI = "doi:10.1007/978-3-030-45093-9_47",
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abstract = "The main idea of this paper is to use Simple Symbolic
Formulas generated offline with the help of the
deterministic function extraction algorithm as building
blocks for Genetic Programming. This idea comparison to
Automatically Defined Functions approach was
considered. A possibility to take into consideration an
expert's knowledge about the problem in hand has been
reviewed. In this work a map of building block's set is
generated by means of clustering. All distances between
blocks are calculated offline by using a special metric
for symbolic expressions. A mutation operator in
Genetic Programming was modified for work with this
kind of nodes. The effectiveness of this approach was
evaluated on benchmark as well as on real world
problems.",
- }
Genetic Programming entries for
Mariia Semenkina
Bogdan Burlacu
Michael Affenzeller
Citations