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Structural synthesis of neural network by means of analytic programming

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dc.title Structural synthesis of neural network by means of analytic programming en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Vařacha, Pavel
dc.contributor.author Oplatková, Zuzana
dc.contributor.author Volná, Eva
dc.relation.ispartof MENDEL 2006
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 80-214-3195-4
dc.date.issued 2006
utb.relation.volume 2006-January
utb.relation.issue January
dc.citation.spage 25
dc.citation.epage 30
dc.event.title 12th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2006
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2006-05-31
dc.event.edate 2006-06-02
dc.type conferenceObject
dc.language.iso en
dc.publisher Brno University of Technology
dc.subject Analytic programming en
dc.subject Genetic programming en
dc.subject Grammar evolution en
dc.subject Optimisation en
dc.subject SOMA en
dc.subject Symbolic regression en
dc.description.abstract This contribution is introducing use of a novelty method, which allows solving various problems from symbolic regression domain. An idea of symbolic regression was firstly proposed by J. R. Koza in so called genetic programming and by C. Ryan in grammatical evolution. In this contribution is demonstrated use of novelty method called analytical programming on neural network synthesis with various results. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1005252
utb.identifier.obdid 14553387
utb.identifier.scopus 2-s2.0-84937031849
utb.source d-scopus
dc.date.accessioned 2015-08-14T09:26:20Z
dc.date.available 2015-08-14T09:26:20Z
utb.contributor.internalauthor Zelinka, Ivan
utb.contributor.internalauthor Vařacha, Pavel
utb.contributor.internalauthor Oplatková, Zuzana
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