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  • The contribution focuses on artificial neural networks application for prediction of chemical semi-batch reactor output. There are studied two approaches to prediction. The first methodology uses classical time series prediction apparatus, when the prediction is based on the one signal only. The second approach uses two signals and corresponds to model predictive control methodology. Both predictors are based on artificial multilayered feed-forward neural networks.
  • The contribution focuses on artificial neural networks application for prediction of chemical semi-batch reactor output. There are studied two approaches to prediction. The first methodology uses classical time series prediction apparatus, when the prediction is based on the one signal only. The second approach uses two signals and corresponds to model predictive control methodology. Both predictors are based on artificial multilayered feed-forward neural networks. (en)
Title
  • Prediction of Semi-Batch Reactor Using Multilayered Feed-Forward Neural Networks
  • Prediction of Semi-Batch Reactor Using Multilayered Feed-Forward Neural Networks (en)
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  • Prediction of Semi-Batch Reactor Using Multilayered Feed-Forward Neural Networks
  • Prediction of Semi-Batch Reactor Using Multilayered Feed-Forward Neural Networks (en)
skos:notation
  • RIV/70883521:28110/12:43869325!RIV13-MSM-28110___
http://linked.open...avai/predkladatel
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  • 161039
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  • RIV/70883521:28110/12:43869325
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  • artificial neural network, prediction, chemical reactor (en)
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  • [985B33C9017F]
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  • Recent Researches in Circuits and Systems
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  • Macků, Lubomír
  • Sámek, David
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http://linked.open.../riv/zahajeniAkce
issn
  • 1790-5117
number of pages
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  • WSEAS Press (GR)
https://schema.org/isbn
  • 978-1-61804-108-1
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  • 28110
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