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Neural network synthesis by means of analytic programming-preliminary results

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dc.title Neural network synthesis by means of analytic programming-preliminary results en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Volná, Eva
dc.relation.ispartof MENDEL 2005
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 80-214-3195-4
dc.date.issued 2005
utb.relation.volume 2005-January
utb.relation.issue January
dc.citation.spage 21
dc.citation.epage 26
dc.event.title 11th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2005
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2005-06-15
dc.event.edate 2005-06-17
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. en
utb.faculty Faculty of Technology
dc.identifier.uri http://hdl.handle.net/10563/1005253
utb.identifier.obdid 14053623
utb.identifier.scopus 2-s2.0-84937043117
utb.source d-scopus
dc.date.accessioned 2015-08-14T09:26:21Z
dc.date.available 2015-08-14T09:26:21Z
dc.description.sponsorship 102/03/0070, GACR, Czech Science Foundation; 202/03/0789, GACR, Czech Science Foundation
utb.contributor.internalauthor Zelinka, Ivan
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