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Description
  • Artificial neural networks are commonly used for prediction of various time series, linear and nonlinear systems. Nevertheless, the choice of proper type of artificial neural networks is difficult task, because each class of artificial neural networks has different features and abilities. Aim of this paper is to compare and benchmark four typical categories of artificial neural networks in artificial time series prediction and provide suggestions for this kind of applications.
  • Artificial neural networks are commonly used for prediction of various time series, linear and nonlinear systems. Nevertheless, the choice of proper type of artificial neural networks is difficult task, because each class of artificial neural networks has different features and abilities. Aim of this paper is to compare and benchmark four typical categories of artificial neural networks in artificial time series prediction and provide suggestions for this kind of applications. (en)
Title
  • Comparison of artificial neural networks using prediction benchmarking
  • Comparison of artificial neural networks using prediction benchmarking (en)
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  • Comparison of artificial neural networks using prediction benchmarking
  • Comparison of artificial neural networks using prediction benchmarking (en)
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  • RIV/70883521:28110/11:43866683!RIV12-MSM-28110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM7088352102)
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http://linked.open...aciTvurceVysledku
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http://linked.open...titaPredkladatele
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  • 191068
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  • RIV/70883521:28110/11:43866683
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  • artificial neural network, prediction, time series, benchmark (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F3F9A5A50B48]
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  • Recent Researches in Automatic Control
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http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Maňas, David
  • Sámek, David
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • WSEAS Press
https://schema.org/isbn
  • 978-1-61804-004-6
http://localhost/t...ganizacniJednotka
  • 28110
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