Symbolic regression methods for control system synthesis
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- @InProceedings{Diveev:2014:MED,
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author = "Askat Diveev and David Kazaryan and Elena Sofronova",
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booktitle = "22nd Mediterranean Conference of Control and
Automation (MED 2014)",
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title = "Symbolic regression methods for control system
synthesis",
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year = "2014",
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month = "16-19 " # jun,
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pages = "587--592",
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abstract = "In this paper we use symbolic regression methods for
control system synthesis. We compare three methods:
network operator method, genetic programming and
analytical programming. We developed variational
versions of genetic programming and analytical
programming to improve the search process efficiency.
All the methods perform search over the set of the
small variations of the given basic solution. Search
efficiency depends on the basic solution. We give an
example of control system synthesis for the unmanned
vehicle with the state constraints over the set of the
initial states using these methods.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/MED.2014.6961436",
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notes = "Also known as \cite{6961436}",
- }
Genetic Programming entries for
Askat Diveev
David Kazaryan
Elena A Sofronova
Citations