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Evolutionary synthesis of complex structures - pseudo neural networks for the task of iris dataset classification

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dc.title Evolutionary synthesis of complex structures - pseudo neural networks for the task of iris dataset classification en
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof Advances in Intelligent Systems and Computing
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783319005416
dc.date.issued 2013
utb.relation.volume 210
dc.citation.spage 211
dc.citation.epage 220
dc.type article
dc.language.iso en
dc.publisher Springer en
dc.identifier.doi 10.1007/978-3-319-00542-3_22
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-00542-3_22
dc.description.abstract This research deals with a novel approach to classification. This paper deals with a synthesis of a complex structure which serves as a classifier. Classical artificial neural networks, where a relation between inputs and outputs is based on the mathematical transfer functions and optimized numerical weights, were an inspiration for this work. The proposed method utilizes Analytic Programming (AP) as the tool of the evolutionary symbolic regression. AP synthesizes a whole structure of the relation between inputs and output. Iris data (a known benchmark for classifiers) was used for testing of the proposed method. For experimentation, Differential Evolution for the main procedure and also for meta-evolution version of analytic programming was used. © Springer International Publishing Switzerland 2013. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003434
utb.identifier.obdid 43869947
utb.identifier.scopus 2-s2.0-84880372474
utb.source j-scopus
dc.date.accessioned 2013-08-02T09:10:28Z
dc.date.available 2013-08-02T09:10:28Z
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Zuzana Kominkova Oplatkova and Roman Senkerik Zuzana Kominkova Oplatkova · Roman Senkerik Tomas Bata University in Zlin, Faculty of Applied Informatics, T.G. Masaryka 5555, 760 01 Zlin, Czech Republic e-mail: {senkerik,oplatkova}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.
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