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dc.title | Time series prediction using artificial neural networks: Single and multi-dimensional data | en |
dc.contributor.author | Sámek, David | |
dc.contributor.author | Vařacha, Pavel | |
dc.relation.ispartof | International Journal of Mathematical Models and Methods in Applied Sciences | |
dc.identifier.issn | 1998-0140 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2013 | |
utb.relation.volume | 7 | |
utb.relation.issue | 1 | |
dc.citation.spage | 38 | |
dc.citation.epage | 46 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | North Atlantic University Union (NAUN) | en |
dc.relation.uri | http://www.naun.org/multimedia/NAUN/ijmmas/16-561.pdf | |
dc.subject | Artificial neural network | en |
dc.subject | Benchmark | en |
dc.subject | Multi-dimensional data | en |
dc.subject | Prediction | en |
dc.subject | Time series | en |
dc.description.abstract | The paper studies time series prediction using artificial neural networks. The special attention is paid to the influence of size of the input vector length. Furthermore, the prediction of standard single-dimensional data signal and the prediction of multi-dimensional data signal are compared. The tested artificial networks are as follows: multilayer feed-forward neural network, recurrent Elman neural network, adaptive linear network and radial basis function neural network. | en |
utb.faculty | Faculty of Technology | |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1003087 | |
utb.identifier.obdid | 43869896 | |
utb.identifier.scopus | 2-s2.0-84872129584 | |
utb.source | j-scopus | |
dc.date.accessioned | 2013-02-02T01:12:48Z | |
dc.date.available | 2013-02-02T01:12:48Z | |
utb.contributor.internalauthor | Sámek, David | |
utb.contributor.internalauthor | Vařacha, Pavel | |
utb.fulltext.affiliation | David Samek and Pavel Varacha D. Samek is with the Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin Czech Republic (phone: +420-576-035-157; fax: +420-576-035-176; e-mail: samek@ft.utb.cz). P. Varacha is with the Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin Czech Republic (e-mail: varacha@fai.utb.cz). | |
utb.fulltext.dates | Manuscript received July 30, 2012 Revised version received August 16, 2012 | |
utb.fulltext.sponsorship | This paper is supported by the Internal Grant Agency at TBU in Zlin, project No. IGA/FAI/2012/056 and by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089. | |
utb.fulltext.projects | IGA/FAI/2012/056 | |
utb.fulltext.projects | CZ.1.05/2.1.00/03.0089 | |
utb.fulltext.faculty | Faculty of Technology | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.ou | Department of Production Engineering | |
utb.fulltext.ou | Department of Informatics and Artificial Intelligence |