Neural network synthesis by means of analytic programming-preliminary results

Zelinka, Ivan; Volná, Eva

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