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dc.title | Synthesis of artificial neural networks by evolutionary methods | en |
dc.contributor.author | Zelinka, Ivan | |
dc.contributor.author | Vařacha, Pavel | |
dc.relation.ispartof | DEXA 2007: 18th International Conference on Database and Expert Systems Applications, Proceedings | |
dc.identifier.isbn | 978-0-7695-2932-5 | |
dc.date.issued | 2007 | |
dc.citation.spage | 153 | |
dc.citation.epage | 157 | |
dc.event.title | 18th International Conference on Database and Expert Systems Applications | |
dc.event.location | Regensburg | |
utb.event.state-en | Germany | |
utb.event.state-cs | Německo | |
dc.event.sdate | 2007-09-03 | |
dc.event.edate | 2007-09-07 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | IEEE Computer Society | en |
dc.identifier.doi | 10.1109/DEXA.2007.67 | |
dc.relation.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4312876 | |
dc.description.abstract | This work deals with a problem of synthesis of the artificial neural networks using the evolutional scanning method The basic task to be solved is to create a symbolic regression algorithm on principles of analytic programming, which will be capable of performing a convenient neural network synthesis. The main motivation here is the computerization of such synthesis and discovering so far unknown solutions. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1001922 | |
utb.identifier.obdid | 43865795 | |
utb.identifier.scopus | 2-s2.0-47849123002 | |
utb.identifier.wok | 000250954300032 | |
utb.source | d-wok | |
dc.date.accessioned | 2011-08-09T07:34:14Z | |
dc.date.available | 2011-08-09T07:34:14Z | |
utb.contributor.internalauthor | Zelinka, Ivan | |
utb.contributor.internalauthor | Vařacha, Pavel |